linux-stable/drivers/char/random.c

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// SPDX-License-Identifier: (GPL-2.0 OR BSD-3-Clause)
/*
random: use BLAKE2s instead of SHA1 in extraction This commit addresses one of the lower hanging fruits of the RNG: its usage of SHA1. BLAKE2s is generally faster, and certainly more secure, than SHA1, which has [1] been [2] really [3] very [4] broken [5]. Additionally, the current construction in the RNG doesn't use the full SHA1 function, as specified, and allows overwriting the IV with RDRAND output in an undocumented way, even in the case when RDRAND isn't set to "trusted", which means potential malicious IV choices. And its short length means that keeping only half of it secret when feeding back into the mixer gives us only 2^80 bits of forward secrecy. In other words, not only is the choice of hash function dated, but the use of it isn't really great either. This commit aims to fix both of these issues while also keeping the general structure and semantics as close to the original as possible. Specifically: a) Rather than overwriting the hash IV with RDRAND, we put it into BLAKE2's documented "salt" and "personal" fields, which were specifically created for this type of usage. b) Since this function feeds the full hash result back into the entropy collector, we only return from it half the length of the hash, just as it was done before. This increases the construction's forward secrecy from 2^80 to a much more comfortable 2^128. c) Rather than using the raw "sha1_transform" function alone, we instead use the full proper BLAKE2s function, with finalization. This also has the advantage of supplying 16 bytes at a time rather than SHA1's 10 bytes, which, in addition to having a faster compression function to begin with, means faster extraction in general. On an Intel i7-11850H, this commit makes initial seeding around 131% faster. BLAKE2s itself has the nice property of internally being based on the ChaCha permutation, which the RNG is already using for expansion, so there shouldn't be any issue with newness, funkiness, or surprising CPU behavior, since it's based on something already in use. [1] https://eprint.iacr.org/2005/010.pdf [2] https://www.iacr.org/archive/crypto2005/36210017/36210017.pdf [3] https://eprint.iacr.org/2015/967.pdf [4] https://shattered.io/static/shattered.pdf [5] https://www.usenix.org/system/files/sec20-leurent.pdf Reviewed-by: Theodore Ts'o <tytso@mit.edu> Reviewed-by: Eric Biggers <ebiggers@google.com> Reviewed-by: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2021-12-21 15:31:27 +00:00
* Copyright (C) 2017-2022 Jason A. Donenfeld <Jason@zx2c4.com>. All Rights Reserved.
* Copyright Matt Mackall <mpm@selenic.com>, 2003, 2004, 2005
* Copyright Theodore Ts'o, 1994, 1995, 1996, 1997, 1998, 1999. All rights reserved.
*
* This driver produces cryptographically secure pseudorandom data. It is divided
* into roughly six sections, each with a section header:
*
* - Initialization and readiness waiting.
* - Fast key erasure RNG, the "crng".
* - Entropy accumulation and extraction routines.
* - Entropy collection routines.
* - Userspace reader/writer interfaces.
* - Sysctl interface.
*
* The high level overview is that there is one input pool, into which
* various pieces of data are hashed. Some of that data is then "credited" as
* having a certain number of bits of entropy. When enough bits of entropy are
* available, the hash is finalized and handed as a key to a stream cipher that
* expands it indefinitely for various consumers. This key is periodically
* refreshed as the various entropy collectors, described below, add data to the
* input pool and credit it. There is currently no Fortuna-like scheduler
* involved, which can lead to malicious entropy sources causing a premature
* reseed, and the entropy estimates are, at best, conservative guesses.
*/
#define pr_fmt(fmt) KBUILD_MODNAME ": " fmt
#include <linux/utsname.h>
#include <linux/module.h>
#include <linux/kernel.h>
#include <linux/major.h>
#include <linux/string.h>
#include <linux/fcntl.h>
#include <linux/slab.h>
#include <linux/random.h>
#include <linux/poll.h>
#include <linux/init.h>
#include <linux/fs.h>
#include <linux/blkdev.h>
#include <linux/interrupt.h>
2008-07-24 04:28:13 +00:00
#include <linux/mm.h>
#include <linux/nodemask.h>
#include <linux/spinlock.h>
#include <linux/kthread.h>
#include <linux/percpu.h>
#include <linux/ptrace.h>
#include <linux/workqueue.h>
#include <linux/irq.h>
#include <linux/ratelimit.h>
random: introduce getrandom(2) system call The getrandom(2) system call was requested by the LibreSSL Portable developers. It is analoguous to the getentropy(2) system call in OpenBSD. The rationale of this system call is to provide resiliance against file descriptor exhaustion attacks, where the attacker consumes all available file descriptors, forcing the use of the fallback code where /dev/[u]random is not available. Since the fallback code is often not well-tested, it is better to eliminate this potential failure mode entirely. The other feature provided by this new system call is the ability to request randomness from the /dev/urandom entropy pool, but to block until at least 128 bits of entropy has been accumulated in the /dev/urandom entropy pool. Historically, the emphasis in the /dev/urandom development has been to ensure that urandom pool is initialized as quickly as possible after system boot, and preferably before the init scripts start execution. This is because changing /dev/urandom reads to block represents an interface change that could potentially break userspace which is not acceptable. In practice, on most x86 desktop and server systems, in general the entropy pool can be initialized before it is needed (and in modern kernels, we will printk a warning message if not). However, on an embedded system, this may not be the case. And so with this new interface, we can provide the functionality of blocking until the urandom pool has been initialized. Any userspace program which uses this new functionality must take care to assure that if it is used during the boot process, that it will not cause the init scripts or other portions of the system startup to hang indefinitely. SYNOPSIS #include <linux/random.h> int getrandom(void *buf, size_t buflen, unsigned int flags); DESCRIPTION The system call getrandom() fills the buffer pointed to by buf with up to buflen random bytes which can be used to seed user space random number generators (i.e., DRBG's) or for other cryptographic uses. It should not be used for Monte Carlo simulations or other programs/algorithms which are doing probabilistic sampling. If the GRND_RANDOM flags bit is set, then draw from the /dev/random pool instead of the /dev/urandom pool. The /dev/random pool is limited based on the entropy that can be obtained from environmental noise, so if there is insufficient entropy, the requested number of bytes may not be returned. If there is no entropy available at all, getrandom(2) will either block, or return an error with errno set to EAGAIN if the GRND_NONBLOCK bit is set in flags. If the GRND_RANDOM bit is not set, then the /dev/urandom pool will be used. Unlike using read(2) to fetch data from /dev/urandom, if the urandom pool has not been sufficiently initialized, getrandom(2) will block (or return -1 with the errno set to EAGAIN if the GRND_NONBLOCK bit is set in flags). The getentropy(2) system call in OpenBSD can be emulated using the following function: int getentropy(void *buf, size_t buflen) { int ret; if (buflen > 256) goto failure; ret = getrandom(buf, buflen, 0); if (ret < 0) return ret; if (ret == buflen) return 0; failure: errno = EIO; return -1; } RETURN VALUE On success, the number of bytes that was filled in the buf is returned. This may not be all the bytes requested by the caller via buflen if insufficient entropy was present in the /dev/random pool, or if the system call was interrupted by a signal. On error, -1 is returned, and errno is set appropriately. ERRORS EINVAL An invalid flag was passed to getrandom(2) EFAULT buf is outside the accessible address space. EAGAIN The requested entropy was not available, and getentropy(2) would have blocked if the GRND_NONBLOCK flag was not set. EINTR While blocked waiting for entropy, the call was interrupted by a signal handler; see the description of how interrupted read(2) calls on "slow" devices are handled with and without the SA_RESTART flag in the signal(7) man page. NOTES For small requests (buflen <= 256) getrandom(2) will not return EINTR when reading from the urandom pool once the entropy pool has been initialized, and it will return all of the bytes that have been requested. This is the recommended way to use getrandom(2), and is designed for compatibility with OpenBSD's getentropy() system call. However, if you are using GRND_RANDOM, then getrandom(2) may block until the entropy accounting determines that sufficient environmental noise has been gathered such that getrandom(2) will be operating as a NRBG instead of a DRBG for those people who are working in the NIST SP 800-90 regime. Since it may block for a long time, these guarantees do *not* apply. The user may want to interrupt a hanging process using a signal, so blocking until all of the requested bytes are returned would be unfriendly. For this reason, the user of getrandom(2) MUST always check the return value, in case it returns some error, or if fewer bytes than requested was returned. In the case of !GRND_RANDOM and small request, the latter should never happen, but the careful userspace code (and all crypto code should be careful) should check for this anyway! Finally, unless you are doing long-term key generation (and perhaps not even then), you probably shouldn't be using GRND_RANDOM. The cryptographic algorithms used for /dev/urandom are quite conservative, and so should be sufficient for all purposes. The disadvantage of GRND_RANDOM is that it can block, and the increased complexity required to deal with partially fulfilled getrandom(2) requests. Signed-off-by: Theodore Ts'o <tytso@mit.edu> Reviewed-by: Zach Brown <zab@zabbo.net>
2014-07-17 08:13:05 +00:00
#include <linux/syscalls.h>
#include <linux/completion.h>
#include <linux/uuid.h>
#include <linux/uaccess.h>
#include <crypto/chacha.h>
random: use BLAKE2s instead of SHA1 in extraction This commit addresses one of the lower hanging fruits of the RNG: its usage of SHA1. BLAKE2s is generally faster, and certainly more secure, than SHA1, which has [1] been [2] really [3] very [4] broken [5]. Additionally, the current construction in the RNG doesn't use the full SHA1 function, as specified, and allows overwriting the IV with RDRAND output in an undocumented way, even in the case when RDRAND isn't set to "trusted", which means potential malicious IV choices. And its short length means that keeping only half of it secret when feeding back into the mixer gives us only 2^80 bits of forward secrecy. In other words, not only is the choice of hash function dated, but the use of it isn't really great either. This commit aims to fix both of these issues while also keeping the general structure and semantics as close to the original as possible. Specifically: a) Rather than overwriting the hash IV with RDRAND, we put it into BLAKE2's documented "salt" and "personal" fields, which were specifically created for this type of usage. b) Since this function feeds the full hash result back into the entropy collector, we only return from it half the length of the hash, just as it was done before. This increases the construction's forward secrecy from 2^80 to a much more comfortable 2^128. c) Rather than using the raw "sha1_transform" function alone, we instead use the full proper BLAKE2s function, with finalization. This also has the advantage of supplying 16 bytes at a time rather than SHA1's 10 bytes, which, in addition to having a faster compression function to begin with, means faster extraction in general. On an Intel i7-11850H, this commit makes initial seeding around 131% faster. BLAKE2s itself has the nice property of internally being based on the ChaCha permutation, which the RNG is already using for expansion, so there shouldn't be any issue with newness, funkiness, or surprising CPU behavior, since it's based on something already in use. [1] https://eprint.iacr.org/2005/010.pdf [2] https://www.iacr.org/archive/crypto2005/36210017/36210017.pdf [3] https://eprint.iacr.org/2015/967.pdf [4] https://shattered.io/static/shattered.pdf [5] https://www.usenix.org/system/files/sec20-leurent.pdf Reviewed-by: Theodore Ts'o <tytso@mit.edu> Reviewed-by: Eric Biggers <ebiggers@google.com> Reviewed-by: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2021-12-21 15:31:27 +00:00
#include <crypto/blake2s.h>
#include <asm/processor.h>
#include <asm/irq.h>
#include <asm/irq_regs.h>
#include <asm/io.h>
/*********************************************************************
*
* Initialization and readiness waiting.
*
* Much of the RNG infrastructure is devoted to various dependencies
* being able to wait until the RNG has collected enough entropy and
* is ready for safe consumption.
*
*********************************************************************/
/*
* crng_init = 0 --> Uninitialized
* 1 --> Initialized
* 2 --> Initialized from input_pool
*
* crng_init is protected by base_crng->lock, and only increases
* its value (from 0->1->2).
*/
static int crng_init = 0;
#define crng_ready() (likely(crng_init > 1))
/* Various types of waiters for crng_init->2 transition. */
static DECLARE_WAIT_QUEUE_HEAD(crng_init_wait);
static struct fasync_struct *fasync;
static DEFINE_SPINLOCK(random_ready_chain_lock);
static RAW_NOTIFIER_HEAD(random_ready_chain);
/* Control how we warn userspace. */
static struct ratelimit_state unseeded_warning =
RATELIMIT_STATE_INIT("warn_unseeded_randomness", HZ, 3);
static struct ratelimit_state urandom_warning =
RATELIMIT_STATE_INIT("warn_urandom_randomness", HZ, 3);
static int ratelimit_disable __read_mostly;
module_param_named(ratelimit_disable, ratelimit_disable, int, 0644);
MODULE_PARM_DESC(ratelimit_disable, "Disable random ratelimit suppression");
/*
* Returns whether or not the input pool has been seeded and thus guaranteed
* to supply cryptographically secure random numbers. This applies to: the
* /dev/urandom device, the get_random_bytes function, and the get_random_{u32,
* ,u64,int,long} family of functions.
*
* Returns: true if the input pool has been seeded.
* false if the input pool has not been seeded.
*/
bool rng_is_initialized(void)
{
return crng_ready();
}
EXPORT_SYMBOL(rng_is_initialized);
/* Used by wait_for_random_bytes(), and considered an entropy collector, below. */
static void try_to_generate_entropy(void);
/*
* Wait for the input pool to be seeded and thus guaranteed to supply
* cryptographically secure random numbers. This applies to: the /dev/urandom
* device, the get_random_bytes function, and the get_random_{u32,u64,int,long}
* family of functions. Using any of these functions without first calling
* this function forfeits the guarantee of security.
*
* Returns: 0 if the input pool has been seeded.
* -ERESTARTSYS if the function was interrupted by a signal.
*/
int wait_for_random_bytes(void)
{
while (!crng_ready()) {
int ret;
try_to_generate_entropy();
ret = wait_event_interruptible_timeout(crng_init_wait, crng_ready(), HZ);
if (ret)
return ret > 0 ? 0 : ret;
}
return 0;
}
EXPORT_SYMBOL(wait_for_random_bytes);
/*
* Add a callback function that will be invoked when the input
* pool is initialised.
*
* returns: 0 if callback is successfully added
* -EALREADY if pool is already initialised (callback not called)
*/
int register_random_ready_notifier(struct notifier_block *nb)
{
unsigned long flags;
int ret = -EALREADY;
if (crng_ready())
return ret;
spin_lock_irqsave(&random_ready_chain_lock, flags);
if (!crng_ready())
ret = raw_notifier_chain_register(&random_ready_chain, nb);
spin_unlock_irqrestore(&random_ready_chain_lock, flags);
return ret;
}
/*
* Delete a previously registered readiness callback function.
*/
int unregister_random_ready_notifier(struct notifier_block *nb)
{
unsigned long flags;
int ret;
spin_lock_irqsave(&random_ready_chain_lock, flags);
ret = raw_notifier_chain_unregister(&random_ready_chain, nb);
spin_unlock_irqrestore(&random_ready_chain_lock, flags);
return ret;
}
static void process_random_ready_list(void)
{
unsigned long flags;
spin_lock_irqsave(&random_ready_chain_lock, flags);
raw_notifier_call_chain(&random_ready_chain, 0, NULL);
spin_unlock_irqrestore(&random_ready_chain_lock, flags);
}
#define warn_unseeded_randomness(previous) \
_warn_unseeded_randomness(__func__, (void *)_RET_IP_, (previous))
static void _warn_unseeded_randomness(const char *func_name, void *caller, void **previous)
{
#ifdef CONFIG_WARN_ALL_UNSEEDED_RANDOM
const bool print_once = false;
#else
static bool print_once __read_mostly;
#endif
if (print_once || crng_ready() ||
(previous && (caller == READ_ONCE(*previous))))
return;
WRITE_ONCE(*previous, caller);
#ifndef CONFIG_WARN_ALL_UNSEEDED_RANDOM
print_once = true;
#endif
if (__ratelimit(&unseeded_warning))
printk_deferred(KERN_NOTICE "random: %s called from %pS with crng_init=%d\n",
func_name, caller, crng_init);
}
/*********************************************************************
*
* Fast key erasure RNG, the "crng".
*
* These functions expand entropy from the entropy extractor into
* long streams for external consumption using the "fast key erasure"
* RNG described at <https://blog.cr.yp.to/20170723-random.html>.
*
* There are a few exported interfaces for use by other drivers:
*
* void get_random_bytes(void *buf, size_t nbytes)
* u32 get_random_u32()
* u64 get_random_u64()
* unsigned int get_random_int()
* unsigned long get_random_long()
*
* These interfaces will return the requested number of random bytes
* into the given buffer or as a return value. This is equivalent to
* a read from /dev/urandom. The u32, u64, int, and long family of
* functions may be higher performance for one-off random integers,
* because they do a bit of buffering and do not invoke reseeding
* until the buffer is emptied.
*
*********************************************************************/
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
enum {
CRNG_RESEED_INTERVAL = 300 * HZ,
CRNG_INIT_CNT_THRESH = 2 * CHACHA_KEY_SIZE
};
static struct {
u8 key[CHACHA_KEY_SIZE] __aligned(__alignof__(long));
unsigned long birth;
unsigned long generation;
spinlock_t lock;
} base_crng = {
.lock = __SPIN_LOCK_UNLOCKED(base_crng.lock)
};
struct crng {
u8 key[CHACHA_KEY_SIZE];
unsigned long generation;
local_lock_t lock;
};
static DEFINE_PER_CPU(struct crng, crngs) = {
.generation = ULONG_MAX,
.lock = INIT_LOCAL_LOCK(crngs.lock),
};
/* Used by crng_reseed() to extract a new seed from the input pool. */
static bool drain_entropy(void *buf, size_t nbytes, bool force);
/*
* This extracts a new crng key from the input pool, but only if there is a
* sufficient amount of entropy available or force is true, in order to
* mitigate bruteforcing of newly added bits.
*/
static void crng_reseed(bool force)
{
unsigned long flags;
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
unsigned long next_gen;
u8 key[CHACHA_KEY_SIZE];
bool finalize_init = false;
/* Only reseed if we can, to prevent brute forcing a small amount of new bits. */
if (!drain_entropy(key, sizeof(key), force))
return;
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
/*
* We copy the new key into the base_crng, overwriting the old one,
* and update the generation counter. We avoid hitting ULONG_MAX,
* because the per-cpu crngs are initialized to ULONG_MAX, so this
* forces new CPUs that come online to always initialize.
*/
spin_lock_irqsave(&base_crng.lock, flags);
memcpy(base_crng.key, key, sizeof(base_crng.key));
next_gen = base_crng.generation + 1;
if (next_gen == ULONG_MAX)
++next_gen;
WRITE_ONCE(base_crng.generation, next_gen);
WRITE_ONCE(base_crng.birth, jiffies);
if (!crng_ready()) {
crng_init = 2;
finalize_init = true;
}
spin_unlock_irqrestore(&base_crng.lock, flags);
memzero_explicit(key, sizeof(key));
if (finalize_init) {
process_random_ready_list();
wake_up_interruptible(&crng_init_wait);
kill_fasync(&fasync, SIGIO, POLL_IN);
pr_notice("crng init done\n");
if (unseeded_warning.missed) {
pr_notice("%d get_random_xx warning(s) missed due to ratelimiting\n",
unseeded_warning.missed);
unseeded_warning.missed = 0;
}
if (urandom_warning.missed) {
pr_notice("%d urandom warning(s) missed due to ratelimiting\n",
urandom_warning.missed);
urandom_warning.missed = 0;
}
}
}
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
/*
* This generates a ChaCha block using the provided key, and then
* immediately overwites that key with half the block. It returns
* the resultant ChaCha state to the user, along with the second
* half of the block containing 32 bytes of random data that may
* be used; random_data_len may not be greater than 32.
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
*/
static void crng_fast_key_erasure(u8 key[CHACHA_KEY_SIZE],
u32 chacha_state[CHACHA_STATE_WORDS],
u8 *random_data, size_t random_data_len)
{
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
u8 first_block[CHACHA_BLOCK_SIZE];
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
BUG_ON(random_data_len > 32);
chacha_init_consts(chacha_state);
memcpy(&chacha_state[4], key, CHACHA_KEY_SIZE);
memset(&chacha_state[12], 0, sizeof(u32) * 4);
chacha20_block(chacha_state, first_block);
memcpy(key, first_block, CHACHA_KEY_SIZE);
memcpy(random_data, first_block + CHACHA_KEY_SIZE, random_data_len);
memzero_explicit(first_block, sizeof(first_block));
}
random: reseed more often immediately after booting In order to chip away at the "premature first" problem, we augment our existing entropy accounting with more frequent reseedings at boot. The idea is that at boot, we're getting entropy from various places, and we're not very sure which of early boot entropy is good and which isn't. Even when we're crediting the entropy, we're still not totally certain that it's any good. Since boot is the one time (aside from a compromise) that we have zero entropy, it's important that we shepherd entropy into the crng fairly often. At the same time, we don't want a "premature next" problem, whereby an attacker can brute force individual bits of added entropy. In lieu of going full-on Fortuna (for now), we can pick a simpler strategy of just reseeding more often during the first 5 minutes after boot. This is still bounded by the 256-bit entropy credit requirement, so we'll skip a reseeding if we haven't reached that, but in case entropy /is/ coming in, this ensures that it makes its way into the crng rather rapidly during these early stages. Ordinarily we reseed if the previous reseeding is 300 seconds old. This commit changes things so that for the first 600 seconds of boot time, we reseed if the previous reseeding is uptime / 2 seconds old. That means that we'll reseed at the very least double the uptime of the previous reseeding. Cc: Theodore Ts'o <tytso@mit.edu> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-03-09 06:32:34 +00:00
/*
* Return whether the crng seed is considered to be sufficiently
* old that a reseeding might be attempted. This happens if the last
* reseeding was CRNG_RESEED_INTERVAL ago, or during early boot, at
* an interval proportional to the uptime.
*/
static bool crng_has_old_seed(void)
{
static bool early_boot = true;
unsigned long interval = CRNG_RESEED_INTERVAL;
if (unlikely(READ_ONCE(early_boot))) {
time64_t uptime = ktime_get_seconds();
if (uptime >= CRNG_RESEED_INTERVAL / HZ * 2)
WRITE_ONCE(early_boot, false);
else
interval = max_t(unsigned int, 5 * HZ,
(unsigned int)uptime / 2 * HZ);
}
return time_after(jiffies, READ_ONCE(base_crng.birth) + interval);
}
/*
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
* This function returns a ChaCha state that you may use for generating
* random data. It also returns up to 32 bytes on its own of random data
* that may be used; random_data_len may not be greater than 32.
*/
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
static void crng_make_state(u32 chacha_state[CHACHA_STATE_WORDS],
u8 *random_data, size_t random_data_len)
{
unsigned long flags;
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
struct crng *crng;
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
BUG_ON(random_data_len > 32);
/*
* For the fast path, we check whether we're ready, unlocked first, and
* then re-check once locked later. In the case where we're really not
* ready, we do fast key erasure with the base_crng directly, because
* this is what crng_pre_init_inject() mutates during early init.
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
*/
if (!crng_ready()) {
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
bool ready;
spin_lock_irqsave(&base_crng.lock, flags);
ready = crng_ready();
if (!ready)
crng_fast_key_erasure(base_crng.key, chacha_state,
random_data, random_data_len);
spin_unlock_irqrestore(&base_crng.lock, flags);
if (!ready)
return;
}
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
/*
random: reseed more often immediately after booting In order to chip away at the "premature first" problem, we augment our existing entropy accounting with more frequent reseedings at boot. The idea is that at boot, we're getting entropy from various places, and we're not very sure which of early boot entropy is good and which isn't. Even when we're crediting the entropy, we're still not totally certain that it's any good. Since boot is the one time (aside from a compromise) that we have zero entropy, it's important that we shepherd entropy into the crng fairly often. At the same time, we don't want a "premature next" problem, whereby an attacker can brute force individual bits of added entropy. In lieu of going full-on Fortuna (for now), we can pick a simpler strategy of just reseeding more often during the first 5 minutes after boot. This is still bounded by the 256-bit entropy credit requirement, so we'll skip a reseeding if we haven't reached that, but in case entropy /is/ coming in, this ensures that it makes its way into the crng rather rapidly during these early stages. Ordinarily we reseed if the previous reseeding is 300 seconds old. This commit changes things so that for the first 600 seconds of boot time, we reseed if the previous reseeding is uptime / 2 seconds old. That means that we'll reseed at the very least double the uptime of the previous reseeding. Cc: Theodore Ts'o <tytso@mit.edu> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-03-09 06:32:34 +00:00
* If the base_crng is old enough, we try to reseed, which in turn
* bumps the generation counter that we check below.
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
*/
random: reseed more often immediately after booting In order to chip away at the "premature first" problem, we augment our existing entropy accounting with more frequent reseedings at boot. The idea is that at boot, we're getting entropy from various places, and we're not very sure which of early boot entropy is good and which isn't. Even when we're crediting the entropy, we're still not totally certain that it's any good. Since boot is the one time (aside from a compromise) that we have zero entropy, it's important that we shepherd entropy into the crng fairly often. At the same time, we don't want a "premature next" problem, whereby an attacker can brute force individual bits of added entropy. In lieu of going full-on Fortuna (for now), we can pick a simpler strategy of just reseeding more often during the first 5 minutes after boot. This is still bounded by the 256-bit entropy credit requirement, so we'll skip a reseeding if we haven't reached that, but in case entropy /is/ coming in, this ensures that it makes its way into the crng rather rapidly during these early stages. Ordinarily we reseed if the previous reseeding is 300 seconds old. This commit changes things so that for the first 600 seconds of boot time, we reseed if the previous reseeding is uptime / 2 seconds old. That means that we'll reseed at the very least double the uptime of the previous reseeding. Cc: Theodore Ts'o <tytso@mit.edu> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-03-09 06:32:34 +00:00
if (unlikely(crng_has_old_seed()))
crng_reseed(false);
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
local_lock_irqsave(&crngs.lock, flags);
crng = raw_cpu_ptr(&crngs);
/*
* If our per-cpu crng is older than the base_crng, then it means
* somebody reseeded the base_crng. In that case, we do fast key
* erasure on the base_crng, and use its output as the new key
* for our per-cpu crng. This brings us up to date with base_crng.
*/
if (unlikely(crng->generation != READ_ONCE(base_crng.generation))) {
spin_lock(&base_crng.lock);
crng_fast_key_erasure(base_crng.key, chacha_state,
crng->key, sizeof(crng->key));
crng->generation = base_crng.generation;
spin_unlock(&base_crng.lock);
}
/*
* Finally, when we've made it this far, our per-cpu crng has an up
* to date key, and we can do fast key erasure with it to produce
* some random data and a ChaCha state for the caller. All other
* branches of this function are "unlikely", so most of the time we
* should wind up here immediately.
*/
crng_fast_key_erasure(crng->key, chacha_state, random_data, random_data_len);
local_unlock_irqrestore(&crngs.lock, flags);
}
/*
* This function is for crng_init == 0 only. It loads entropy directly
* into the crng's key, without going through the input pool. It is,
* generally speaking, not very safe, but we use this only at early
* boot time when it's better to have something there rather than
* nothing.
*
* If account is set, then the crng_init_cnt counter is incremented.
* This shouldn't be set by functions like add_device_randomness(),
* where we can't trust the buffer passed to it is guaranteed to be
* unpredictable (so it might not have any entropy at all).
*
* Returns the number of bytes processed from input, which is bounded
* by CRNG_INIT_CNT_THRESH if account is true.
*/
2022-02-13 17:25:07 +00:00
static size_t crng_pre_init_inject(const void *input, size_t len, bool account)
{
static int crng_init_cnt = 0;
2022-02-13 17:25:07 +00:00
struct blake2s_state hash;
unsigned long flags;
2022-02-13 17:25:07 +00:00
blake2s_init(&hash, sizeof(base_crng.key));
2022-02-13 17:25:07 +00:00
spin_lock_irqsave(&base_crng.lock, flags);
if (crng_init != 0) {
spin_unlock_irqrestore(&base_crng.lock, flags);
return 0;
}
if (account)
len = min_t(size_t, len, CRNG_INIT_CNT_THRESH - crng_init_cnt);
2022-02-13 17:25:07 +00:00
blake2s_update(&hash, base_crng.key, sizeof(base_crng.key));
blake2s_update(&hash, input, len);
blake2s_final(&hash, base_crng.key);
if (account) {
crng_init_cnt += len;
if (crng_init_cnt >= CRNG_INIT_CNT_THRESH) {
++base_crng.generation;
crng_init = 1;
}
}
spin_unlock_irqrestore(&base_crng.lock, flags);
if (crng_init == 1)
pr_notice("fast init done\n");
return len;
}
static void _get_random_bytes(void *buf, size_t nbytes)
{
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
u32 chacha_state[CHACHA_STATE_WORDS];
u8 tmp[CHACHA_BLOCK_SIZE];
size_t len;
if (!nbytes)
return;
len = min_t(size_t, 32, nbytes);
crng_make_state(chacha_state, buf, len);
nbytes -= len;
buf += len;
while (nbytes) {
if (nbytes < CHACHA_BLOCK_SIZE) {
chacha20_block(chacha_state, tmp);
memcpy(buf, tmp, nbytes);
memzero_explicit(tmp, sizeof(tmp));
break;
}
chacha20_block(chacha_state, buf);
if (unlikely(chacha_state[12] == 0))
++chacha_state[13];
nbytes -= CHACHA_BLOCK_SIZE;
buf += CHACHA_BLOCK_SIZE;
}
memzero_explicit(chacha_state, sizeof(chacha_state));
}
/*
* This function is the exported kernel interface. It returns some
* number of good random numbers, suitable for key generation, seeding
* TCP sequence numbers, etc. It does not rely on the hardware random
* number generator. For random bytes direct from the hardware RNG
* (when available), use get_random_bytes_arch(). In order to ensure
* that the randomness provided by this function is okay, the function
* wait_for_random_bytes() should be called and return 0 at least once
* at any point prior.
*/
void get_random_bytes(void *buf, size_t nbytes)
{
static void *previous;
warn_unseeded_randomness(&previous);
_get_random_bytes(buf, nbytes);
}
EXPORT_SYMBOL(get_random_bytes);
static ssize_t get_random_bytes_user(void __user *buf, size_t nbytes)
{
bool large_request = nbytes > 256;
ssize_t ret = 0;
size_t len;
u32 chacha_state[CHACHA_STATE_WORDS];
u8 output[CHACHA_BLOCK_SIZE];
if (!nbytes)
return 0;
len = min_t(size_t, 32, nbytes);
crng_make_state(chacha_state, output, len);
if (copy_to_user(buf, output, len))
return -EFAULT;
nbytes -= len;
buf += len;
ret += len;
while (nbytes) {
if (large_request && need_resched()) {
if (signal_pending(current))
break;
schedule();
}
chacha20_block(chacha_state, output);
if (unlikely(chacha_state[12] == 0))
++chacha_state[13];
len = min_t(size_t, nbytes, CHACHA_BLOCK_SIZE);
if (copy_to_user(buf, output, len)) {
ret = -EFAULT;
break;
}
nbytes -= len;
buf += len;
ret += len;
}
memzero_explicit(chacha_state, sizeof(chacha_state));
memzero_explicit(output, sizeof(output));
return ret;
}
/*
* Batched entropy returns random integers. The quality of the random
* number is good as /dev/urandom. In order to ensure that the randomness
* provided by this function is okay, the function wait_for_random_bytes()
* should be called and return 0 at least once at any point prior.
*/
struct batched_entropy {
union {
/*
* We make this 1.5x a ChaCha block, so that we get the
* remaining 32 bytes from fast key erasure, plus one full
* block from the detached ChaCha state. We can increase
* the size of this later if needed so long as we keep the
* formula of (integer_blocks + 0.5) * CHACHA_BLOCK_SIZE.
*/
u64 entropy_u64[CHACHA_BLOCK_SIZE * 3 / (2 * sizeof(u64))];
u32 entropy_u32[CHACHA_BLOCK_SIZE * 3 / (2 * sizeof(u32))];
};
local_lock_t lock;
unsigned long generation;
unsigned int position;
};
static DEFINE_PER_CPU(struct batched_entropy, batched_entropy_u64) = {
.lock = INIT_LOCAL_LOCK(batched_entropy_u64.lock),
.position = UINT_MAX
};
u64 get_random_u64(void)
{
u64 ret;
unsigned long flags;
struct batched_entropy *batch;
static void *previous;
unsigned long next_gen;
warn_unseeded_randomness(&previous);
local_lock_irqsave(&batched_entropy_u64.lock, flags);
batch = raw_cpu_ptr(&batched_entropy_u64);
next_gen = READ_ONCE(base_crng.generation);
if (batch->position >= ARRAY_SIZE(batch->entropy_u64) ||
next_gen != batch->generation) {
_get_random_bytes(batch->entropy_u64, sizeof(batch->entropy_u64));
batch->position = 0;
batch->generation = next_gen;
}
ret = batch->entropy_u64[batch->position];
batch->entropy_u64[batch->position] = 0;
++batch->position;
local_unlock_irqrestore(&batched_entropy_u64.lock, flags);
return ret;
}
EXPORT_SYMBOL(get_random_u64);
static DEFINE_PER_CPU(struct batched_entropy, batched_entropy_u32) = {
.lock = INIT_LOCAL_LOCK(batched_entropy_u32.lock),
.position = UINT_MAX
};
u32 get_random_u32(void)
{
u32 ret;
unsigned long flags;
struct batched_entropy *batch;
static void *previous;
unsigned long next_gen;
warn_unseeded_randomness(&previous);
local_lock_irqsave(&batched_entropy_u32.lock, flags);
batch = raw_cpu_ptr(&batched_entropy_u32);
next_gen = READ_ONCE(base_crng.generation);
if (batch->position >= ARRAY_SIZE(batch->entropy_u32) ||
next_gen != batch->generation) {
_get_random_bytes(batch->entropy_u32, sizeof(batch->entropy_u32));
batch->position = 0;
batch->generation = next_gen;
}
ret = batch->entropy_u32[batch->position];
batch->entropy_u32[batch->position] = 0;
++batch->position;
local_unlock_irqrestore(&batched_entropy_u32.lock, flags);
return ret;
}
EXPORT_SYMBOL(get_random_u32);
#ifdef CONFIG_SMP
/*
* This function is called when the CPU is coming up, with entry
* CPUHP_RANDOM_PREPARE, which comes before CPUHP_WORKQUEUE_PREP.
*/
int random_prepare_cpu(unsigned int cpu)
{
/*
* When the cpu comes back online, immediately invalidate both
* the per-cpu crng and all batches, so that we serve fresh
* randomness.
*/
per_cpu_ptr(&crngs, cpu)->generation = ULONG_MAX;
per_cpu_ptr(&batched_entropy_u32, cpu)->position = UINT_MAX;
per_cpu_ptr(&batched_entropy_u64, cpu)->position = UINT_MAX;
return 0;
}
#endif
/**
* randomize_page - Generate a random, page aligned address
* @start: The smallest acceptable address the caller will take.
* @range: The size of the area, starting at @start, within which the
* random address must fall.
*
* If @start + @range would overflow, @range is capped.
*
* NOTE: Historical use of randomize_range, which this replaces, presumed that
* @start was already page aligned. We now align it regardless.
*
* Return: A page aligned address within [start, start + range). On error,
* @start is returned.
*/
unsigned long randomize_page(unsigned long start, unsigned long range)
{
if (!PAGE_ALIGNED(start)) {
range -= PAGE_ALIGN(start) - start;
start = PAGE_ALIGN(start);
}
if (start > ULONG_MAX - range)
range = ULONG_MAX - start;
range >>= PAGE_SHIFT;
if (range == 0)
return start;
return start + (get_random_long() % range << PAGE_SHIFT);
}
/*
* This function will use the architecture-specific hardware random
* number generator if it is available. It is not recommended for
* use. Use get_random_bytes() instead. It returns the number of
* bytes filled in.
*/
size_t __must_check get_random_bytes_arch(void *buf, size_t nbytes)
{
size_t left = nbytes;
u8 *p = buf;
while (left) {
unsigned long v;
size_t chunk = min_t(size_t, left, sizeof(unsigned long));
if (!arch_get_random_long(&v))
break;
memcpy(p, &v, chunk);
p += chunk;
left -= chunk;
}
return nbytes - left;
}
EXPORT_SYMBOL(get_random_bytes_arch);
/**********************************************************************
*
* Entropy accumulation and extraction routines.
*
* Callers may add entropy via:
*
* static void mix_pool_bytes(const void *in, size_t nbytes)
*
* After which, if added entropy should be credited:
*
* static void credit_entropy_bits(size_t nbits)
*
* Finally, extract entropy via these two, with the latter one
* setting the entropy count to zero and extracting only if there
* is POOL_MIN_BITS entropy credited prior or force is true:
*
* static void extract_entropy(void *buf, size_t nbytes)
* static bool drain_entropy(void *buf, size_t nbytes, bool force)
*
**********************************************************************/
enum {
POOL_BITS = BLAKE2S_HASH_SIZE * 8,
POOL_MIN_BITS = POOL_BITS /* No point in settling for less. */
};
/* For notifying userspace should write into /dev/random. */
static DECLARE_WAIT_QUEUE_HEAD(random_write_wait);
static struct {
struct blake2s_state hash;
spinlock_t lock;
unsigned int entropy_count;
} input_pool = {
.hash.h = { BLAKE2S_IV0 ^ (0x01010000 | BLAKE2S_HASH_SIZE),
BLAKE2S_IV1, BLAKE2S_IV2, BLAKE2S_IV3, BLAKE2S_IV4,
BLAKE2S_IV5, BLAKE2S_IV6, BLAKE2S_IV7 },
.hash.outlen = BLAKE2S_HASH_SIZE,
.lock = __SPIN_LOCK_UNLOCKED(input_pool.lock),
};
static void _mix_pool_bytes(const void *in, size_t nbytes)
{
blake2s_update(&input_pool.hash, in, nbytes);
}
/*
* This function adds bytes into the entropy "pool". It does not
* update the entropy estimate. The caller should call
* credit_entropy_bits if this is appropriate.
*/
static void mix_pool_bytes(const void *in, size_t nbytes)
{
unsigned long flags;
spin_lock_irqsave(&input_pool.lock, flags);
_mix_pool_bytes(in, nbytes);
spin_unlock_irqrestore(&input_pool.lock, flags);
}
static void credit_entropy_bits(size_t nbits)
{
unsigned int entropy_count, orig, add;
if (!nbits)
return;
add = min_t(size_t, nbits, POOL_BITS);
do {
orig = READ_ONCE(input_pool.entropy_count);
entropy_count = min_t(unsigned int, POOL_BITS, orig + add);
} while (cmpxchg(&input_pool.entropy_count, orig, entropy_count) != orig);
if (!crng_ready() && entropy_count >= POOL_MIN_BITS)
crng_reseed(false);
}
/*
* This is an HKDF-like construction for using the hashed collected entropy
* as a PRF key, that's then expanded block-by-block.
*/
static void extract_entropy(void *buf, size_t nbytes)
{
unsigned long flags;
u8 seed[BLAKE2S_HASH_SIZE], next_key[BLAKE2S_HASH_SIZE];
struct {
unsigned long rdseed[32 / sizeof(long)];
size_t counter;
} block;
size_t i;
for (i = 0; i < ARRAY_SIZE(block.rdseed); ++i) {
if (!arch_get_random_seed_long(&block.rdseed[i]) &&
!arch_get_random_long(&block.rdseed[i]))
block.rdseed[i] = random_get_entropy();
}
spin_lock_irqsave(&input_pool.lock, flags);
/* seed = HASHPRF(last_key, entropy_input) */
blake2s_final(&input_pool.hash, seed);
/* next_key = HASHPRF(seed, RDSEED || 0) */
block.counter = 0;
blake2s(next_key, (u8 *)&block, seed, sizeof(next_key), sizeof(block), sizeof(seed));
blake2s_init_key(&input_pool.hash, BLAKE2S_HASH_SIZE, next_key, sizeof(next_key));
spin_unlock_irqrestore(&input_pool.lock, flags);
memzero_explicit(next_key, sizeof(next_key));
while (nbytes) {
i = min_t(size_t, nbytes, BLAKE2S_HASH_SIZE);
/* output = HASHPRF(seed, RDSEED || ++counter) */
++block.counter;
blake2s(buf, (u8 *)&block, seed, i, sizeof(block), sizeof(seed));
nbytes -= i;
buf += i;
}
memzero_explicit(seed, sizeof(seed));
memzero_explicit(&block, sizeof(block));
}
/*
* First we make sure we have POOL_MIN_BITS of entropy in the pool unless force
* is true, and then we set the entropy count to zero (but don't actually touch
* any data). Only then can we extract a new key with extract_entropy().
*/
static bool drain_entropy(void *buf, size_t nbytes, bool force)
{
unsigned int entropy_count;
do {
entropy_count = READ_ONCE(input_pool.entropy_count);
if (!force && entropy_count < POOL_MIN_BITS)
return false;
} while (cmpxchg(&input_pool.entropy_count, entropy_count, 0) != entropy_count);
extract_entropy(buf, nbytes);
wake_up_interruptible(&random_write_wait);
kill_fasync(&fasync, SIGIO, POLL_OUT);
return true;
}
/**********************************************************************
*
* Entropy collection routines.
*
* The following exported functions are used for pushing entropy into
* the above entropy accumulation routines:
*
* void add_device_randomness(const void *buf, size_t size);
* void add_input_randomness(unsigned int type, unsigned int code,
* unsigned int value);
* void add_disk_randomness(struct gendisk *disk);
* void add_hwgenerator_randomness(const void *buffer, size_t count,
* size_t entropy);
* void add_bootloader_randomness(const void *buf, size_t size);
* void add_vmfork_randomness(const void *unique_vm_id, size_t size);
* void add_interrupt_randomness(int irq);
*
* add_device_randomness() adds data to the input pool that
* is likely to differ between two devices (or possibly even per boot).
* This would be things like MAC addresses or serial numbers, or the
* read-out of the RTC. This does *not* credit any actual entropy to
* the pool, but it initializes the pool to different values for devices
* that might otherwise be identical and have very little entropy
* available to them (particularly common in the embedded world).
*
* add_input_randomness() uses the input layer interrupt timing, as well
* as the event type information from the hardware.
*
* add_disk_randomness() uses what amounts to the seek time of block
* layer request events, on a per-disk_devt basis, as input to the
* entropy pool. Note that high-speed solid state drives with very low
* seek times do not make for good sources of entropy, as their seek
* times are usually fairly consistent.
*
* The above two routines try to estimate how many bits of entropy
* to credit. They do this by keeping track of the first and second
* order deltas of the event timings.
*
* add_hwgenerator_randomness() is for true hardware RNGs, and will credit
* entropy as specified by the caller. If the entropy pool is full it will
* block until more entropy is needed.
*
* add_bootloader_randomness() is the same as add_hwgenerator_randomness() or
* add_device_randomness(), depending on whether or not the configuration
* option CONFIG_RANDOM_TRUST_BOOTLOADER is set.
*
* add_vmfork_randomness() adds a unique (but not necessarily secret) ID
* representing the current instance of a VM to the pool, without crediting,
* and then force-reseeds the crng so that it takes effect immediately.
*
* add_interrupt_randomness() uses the interrupt timing as random
* inputs to the entropy pool. Using the cycle counters and the irq source
* as inputs, it feeds the input pool roughly once a second or after 64
* interrupts, crediting 1 bit of entropy for whichever comes first.
*
**********************************************************************/
static bool trust_cpu __ro_after_init = IS_ENABLED(CONFIG_RANDOM_TRUST_CPU);
static bool trust_bootloader __ro_after_init = IS_ENABLED(CONFIG_RANDOM_TRUST_BOOTLOADER);
static int __init parse_trust_cpu(char *arg)
{
return kstrtobool(arg, &trust_cpu);
}
static int __init parse_trust_bootloader(char *arg)
{
return kstrtobool(arg, &trust_bootloader);
}
early_param("random.trust_cpu", parse_trust_cpu);
early_param("random.trust_bootloader", parse_trust_bootloader);
/*
* The first collection of entropy occurs at system boot while interrupts
* are still turned off. Here we push in RDSEED, a timestamp, and utsname().
* Depending on the above configuration knob, RDSEED may be considered
* sufficient for initialization. Note that much earlier setup may already
* have pushed entropy into the input pool by the time we get here.
*/
int __init rand_initialize(void)
{
size_t i;
ktime_t now = ktime_get_real();
bool arch_init = true;
unsigned long rv;
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
#if defined(LATENT_ENTROPY_PLUGIN)
static const u8 compiletime_seed[BLAKE2S_BLOCK_SIZE] __initconst __latent_entropy;
_mix_pool_bytes(compiletime_seed, sizeof(compiletime_seed));
#endif
for (i = 0; i < BLAKE2S_BLOCK_SIZE; i += sizeof(rv)) {
if (!arch_get_random_seed_long_early(&rv) &&
!arch_get_random_long_early(&rv)) {
rv = random_get_entropy();
arch_init = false;
}
_mix_pool_bytes(&rv, sizeof(rv));
}
_mix_pool_bytes(&now, sizeof(now));
_mix_pool_bytes(utsname(), sizeof(*(utsname())));
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
extract_entropy(base_crng.key, sizeof(base_crng.key));
++base_crng.generation;
random: use simpler fast key erasure flow on per-cpu keys Rather than the clunky NUMA full ChaCha state system we had prior, this commit is closer to the original "fast key erasure RNG" proposal from <https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha keys on a per-cpu basis. All entropy is extracted to a base crng key of 32 bytes. This base crng has a birthdate and a generation counter. When we go to take bytes from the crng, we first check if the birthdate is too old; if it is, we reseed per usual. Then we start working on a per-cpu crng. This per-cpu crng makes sure that it has the same generation counter as the base crng. If it doesn't, it does fast key erasure with the base crng key and uses the output as its new per-cpu key, and then updates its local generation counter. Then, using this per-cpu state, we do ordinary fast key erasure. Half of this first block is used to overwrite the per-cpu crng key for the next call -- this is the fast key erasure RNG idea -- and the other half, along with the ChaCha state, is returned to the caller. If the caller desires more than this remaining half, it can generate more ChaCha blocks, unlocked, using the now detached ChaCha state that was just returned. Crypto-wise, this is more or less what we were doing before, but this simply makes it more explicit and ensures that we always have backtrack protection by not playing games with a shared block counter. The flow looks like this: ──extract()──► base_crng.key ◄──memcpy()───┐ │ │ └──chacha()──────┬─► new_base_key └─► crngs[n].key ◄──memcpy()───┐ │ │ └──chacha()───┬─► new_key └─► random_bytes │ └────► There are a few hairy details around early init. Just as was done before, prior to having gathered enough entropy, crng_fast_load() and crng_slow_load() dump bytes directly into the base crng, and when we go to take bytes from the crng, in that case, we're doing fast key erasure with the base crng rather than the fast unlocked per-cpu crngs. This is fine as that's only the state of affairs during very early boot; once the crng initializes we never use these paths again. In the process of all this, the APIs into the crng become a bit simpler: we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len), which both do what you'd expect. All of the details of fast key erasure and per-cpu selection happen only in a very short critical section of crng_make_state(), which selects the right per-cpu key, does the fast key erasure, and returns a local state to the caller's stack. So, we no longer have a need for a separate backtrack function, as this happens all at once here. The API then allows us to extend backtrack protection to batched entropy without really having to do much at all. The result is a bit simpler than before and has fewer foot guns. The init time state machine also gets a lot simpler as we don't need to wait for workqueues to come online and do deferred work. And the multi-core performance should be increased significantly, by virtue of having hardly any locking on the fast path. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Jann Horn <jannh@google.com> Reviewed-by: Eric Biggers <ebiggers@google.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 14:08:49 +00:00
if (arch_init && trust_cpu && !crng_ready()) {
crng_init = 2;
pr_notice("crng init done (trusting CPU's manufacturer)\n");
}
if (ratelimit_disable) {
urandom_warning.interval = 0;
unseeded_warning.interval = 0;
}
return 0;
}
/*
* Add device- or boot-specific data to the input pool to help
* initialize it.
*
* None of this adds any entropy; it is meant to avoid the problem of
* the entropy pool having similar initial state across largely
* identical devices.
*/
void add_device_randomness(const void *buf, size_t size)
{
cycles_t cycles = random_get_entropy();
unsigned long flags, now = jiffies;
if (crng_init == 0 && size)
2022-02-13 17:25:07 +00:00
crng_pre_init_inject(buf, size, false);
spin_lock_irqsave(&input_pool.lock, flags);
_mix_pool_bytes(&cycles, sizeof(cycles));
_mix_pool_bytes(&now, sizeof(now));
_mix_pool_bytes(buf, size);
spin_unlock_irqrestore(&input_pool.lock, flags);
}
EXPORT_SYMBOL(add_device_randomness);
/* There is one of these per entropy source */
struct timer_rand_state {
unsigned long last_time;
long last_delta, last_delta2;
};
/*
* This function adds entropy to the entropy "pool" by using timing
* delays. It uses the timer_rand_state structure to make an estimate
* of how many bits of entropy this call has added to the pool.
*
* The number "num" is also added to the pool - it should somehow describe
* the type of event which just happened. This is currently 0-255 for
* keyboard scan codes, and 256 upwards for interrupts.
*/
static void add_timer_randomness(struct timer_rand_state *state, unsigned int num)
{
cycles_t cycles = random_get_entropy();
unsigned long flags, now = jiffies;
long delta, delta2, delta3;
spin_lock_irqsave(&input_pool.lock, flags);
_mix_pool_bytes(&cycles, sizeof(cycles));
_mix_pool_bytes(&now, sizeof(now));
_mix_pool_bytes(&num, sizeof(num));
spin_unlock_irqrestore(&input_pool.lock, flags);
/*
* Calculate number of bits of randomness we probably added.
* We take into account the first, second and third-order deltas
* in order to make our estimate.
*/
delta = now - READ_ONCE(state->last_time);
WRITE_ONCE(state->last_time, now);
random: fix data races at timer_rand_state Fields in "struct timer_rand_state" could be accessed concurrently. Lockless plain reads and writes result in data races. Fix them by adding pairs of READ|WRITE_ONCE(). The data races were reported by KCSAN, BUG: KCSAN: data-race in add_timer_randomness / add_timer_randomness write to 0xffff9f320a0a01d0 of 8 bytes by interrupt on cpu 22: add_timer_randomness+0x100/0x190 add_timer_randomness at drivers/char/random.c:1152 add_disk_randomness+0x85/0x280 scsi_end_request+0x43a/0x4a0 scsi_io_completion+0xb7/0x7e0 scsi_finish_command+0x1ed/0x2a0 scsi_softirq_done+0x1c9/0x1d0 blk_done_softirq+0x181/0x1d0 __do_softirq+0xd9/0x57c irq_exit+0xa2/0xc0 do_IRQ+0x8b/0x190 ret_from_intr+0x0/0x42 cpuidle_enter_state+0x15e/0x980 cpuidle_enter+0x69/0xc0 call_cpuidle+0x23/0x40 do_idle+0x248/0x280 cpu_startup_entry+0x1d/0x1f start_secondary+0x1b2/0x230 secondary_startup_64+0xb6/0xc0 no locks held by swapper/22/0. irq event stamp: 32871382 _raw_spin_unlock_irqrestore+0x53/0x60 _raw_spin_lock_irqsave+0x21/0x60 _local_bh_enable+0x21/0x30 irq_exit+0xa2/0xc0 read to 0xffff9f320a0a01d0 of 8 bytes by interrupt on cpu 2: add_timer_randomness+0xe8/0x190 add_disk_randomness+0x85/0x280 scsi_end_request+0x43a/0x4a0 scsi_io_completion+0xb7/0x7e0 scsi_finish_command+0x1ed/0x2a0 scsi_softirq_done+0x1c9/0x1d0 blk_done_softirq+0x181/0x1d0 __do_softirq+0xd9/0x57c irq_exit+0xa2/0xc0 do_IRQ+0x8b/0x190 ret_from_intr+0x0/0x42 cpuidle_enter_state+0x15e/0x980 cpuidle_enter+0x69/0xc0 call_cpuidle+0x23/0x40 do_idle+0x248/0x280 cpu_startup_entry+0x1d/0x1f start_secondary+0x1b2/0x230 secondary_startup_64+0xb6/0xc0 no locks held by swapper/2/0. irq event stamp: 37846304 _raw_spin_unlock_irqrestore+0x53/0x60 _raw_spin_lock_irqsave+0x21/0x60 _local_bh_enable+0x21/0x30 irq_exit+0xa2/0xc0 Reported by Kernel Concurrency Sanitizer on: Hardware name: HP ProLiant BL660c Gen9, BIOS I38 10/17/2018 Link: https://lore.kernel.org/r/1582648024-13111-1-git-send-email-cai@lca.pw Signed-off-by: Qian Cai <cai@lca.pw> Signed-off-by: Theodore Ts'o <tytso@mit.edu>
2020-02-25 16:27:04 +00:00
delta2 = delta - READ_ONCE(state->last_delta);
WRITE_ONCE(state->last_delta, delta);
random: fix data races at timer_rand_state Fields in "struct timer_rand_state" could be accessed concurrently. Lockless plain reads and writes result in data races. Fix them by adding pairs of READ|WRITE_ONCE(). The data races were reported by KCSAN, BUG: KCSAN: data-race in add_timer_randomness / add_timer_randomness write to 0xffff9f320a0a01d0 of 8 bytes by interrupt on cpu 22: add_timer_randomness+0x100/0x190 add_timer_randomness at drivers/char/random.c:1152 add_disk_randomness+0x85/0x280 scsi_end_request+0x43a/0x4a0 scsi_io_completion+0xb7/0x7e0 scsi_finish_command+0x1ed/0x2a0 scsi_softirq_done+0x1c9/0x1d0 blk_done_softirq+0x181/0x1d0 __do_softirq+0xd9/0x57c irq_exit+0xa2/0xc0 do_IRQ+0x8b/0x190 ret_from_intr+0x0/0x42 cpuidle_enter_state+0x15e/0x980 cpuidle_enter+0x69/0xc0 call_cpuidle+0x23/0x40 do_idle+0x248/0x280 cpu_startup_entry+0x1d/0x1f start_secondary+0x1b2/0x230 secondary_startup_64+0xb6/0xc0 no locks held by swapper/22/0. irq event stamp: 32871382 _raw_spin_unlock_irqrestore+0x53/0x60 _raw_spin_lock_irqsave+0x21/0x60 _local_bh_enable+0x21/0x30 irq_exit+0xa2/0xc0 read to 0xffff9f320a0a01d0 of 8 bytes by interrupt on cpu 2: add_timer_randomness+0xe8/0x190 add_disk_randomness+0x85/0x280 scsi_end_request+0x43a/0x4a0 scsi_io_completion+0xb7/0x7e0 scsi_finish_command+0x1ed/0x2a0 scsi_softirq_done+0x1c9/0x1d0 blk_done_softirq+0x181/0x1d0 __do_softirq+0xd9/0x57c irq_exit+0xa2/0xc0 do_IRQ+0x8b/0x190 ret_from_intr+0x0/0x42 cpuidle_enter_state+0x15e/0x980 cpuidle_enter+0x69/0xc0 call_cpuidle+0x23/0x40 do_idle+0x248/0x280 cpu_startup_entry+0x1d/0x1f start_secondary+0x1b2/0x230 secondary_startup_64+0xb6/0xc0 no locks held by swapper/2/0. irq event stamp: 37846304 _raw_spin_unlock_irqrestore+0x53/0x60 _raw_spin_lock_irqsave+0x21/0x60 _local_bh_enable+0x21/0x30 irq_exit+0xa2/0xc0 Reported by Kernel Concurrency Sanitizer on: Hardware name: HP ProLiant BL660c Gen9, BIOS I38 10/17/2018 Link: https://lore.kernel.org/r/1582648024-13111-1-git-send-email-cai@lca.pw Signed-off-by: Qian Cai <cai@lca.pw> Signed-off-by: Theodore Ts'o <tytso@mit.edu>
2020-02-25 16:27:04 +00:00
delta3 = delta2 - READ_ONCE(state->last_delta2);
WRITE_ONCE(state->last_delta2, delta2);
if (delta < 0)
delta = -delta;
if (delta2 < 0)
delta2 = -delta2;
if (delta3 < 0)
delta3 = -delta3;
if (delta > delta2)
delta = delta2;
if (delta > delta3)
delta = delta3;
/*
* delta is now minimum absolute delta.
* Round down by 1 bit on general principles,
* and limit entropy estimate to 12 bits.
*/
credit_entropy_bits(min_t(unsigned int, fls(delta >> 1), 11));
}
void add_input_randomness(unsigned int type, unsigned int code,
unsigned int value)
{
static unsigned char last_value;
static struct timer_rand_state input_timer_state = { INITIAL_JIFFIES };
/* Ignore autorepeat and the like. */
if (value == last_value)
return;
last_value = value;
add_timer_randomness(&input_timer_state,
(type << 4) ^ code ^ (code >> 4) ^ value);
}
EXPORT_SYMBOL_GPL(add_input_randomness);
#ifdef CONFIG_BLOCK
void add_disk_randomness(struct gendisk *disk)
{
if (!disk || !disk->random)
return;
/* First major is 1, so we get >= 0x200 here. */
add_timer_randomness(disk->random, 0x100 + disk_devt(disk));
}
EXPORT_SYMBOL_GPL(add_disk_randomness);
void rand_initialize_disk(struct gendisk *disk)
{
struct timer_rand_state *state;
/*
* If kzalloc returns null, we just won't use that entropy
* source.
*/
state = kzalloc(sizeof(struct timer_rand_state), GFP_KERNEL);
if (state) {
state->last_time = INITIAL_JIFFIES;
disk->random = state;
}
}
#endif
/*
* Interface for in-kernel drivers of true hardware RNGs.
* Those devices may produce endless random bits and will be throttled
* when our pool is full.
*/
void add_hwgenerator_randomness(const void *buffer, size_t count,
size_t entropy)
{
if (unlikely(crng_init == 0 && entropy < POOL_MIN_BITS)) {
2022-02-13 17:25:07 +00:00
size_t ret = crng_pre_init_inject(buffer, count, true);
mix_pool_bytes(buffer, ret);
count -= ret;
buffer += ret;
if (!count || crng_init == 0)
return;
}
/*
* Throttle writing if we're above the trickle threshold.
* We'll be woken up again once below POOL_MIN_BITS, when
* the calling thread is about to terminate, or once
* CRNG_RESEED_INTERVAL has elapsed.
*/
wait_event_interruptible_timeout(random_write_wait,
!system_wq || kthread_should_stop() ||
input_pool.entropy_count < POOL_MIN_BITS,
CRNG_RESEED_INTERVAL);
mix_pool_bytes(buffer, count);
credit_entropy_bits(entropy);
}
EXPORT_SYMBOL_GPL(add_hwgenerator_randomness);
/*
* Handle random seed passed by bootloader.
* If the seed is trustworthy, it would be regarded as hardware RNGs. Otherwise
* it would be regarded as device data.
* The decision is controlled by CONFIG_RANDOM_TRUST_BOOTLOADER.
*/
void add_bootloader_randomness(const void *buf, size_t size)
{
if (trust_bootloader)
add_hwgenerator_randomness(buf, size, size * 8);
else
add_device_randomness(buf, size);
}
EXPORT_SYMBOL_GPL(add_bootloader_randomness);
#if IS_ENABLED(CONFIG_VMGENID)
static BLOCKING_NOTIFIER_HEAD(vmfork_chain);
/*
* Handle a new unique VM ID, which is unique, not secret, so we
* don't credit it, but we do immediately force a reseed after so
* that it's used by the crng posthaste.
*/
void add_vmfork_randomness(const void *unique_vm_id, size_t size)
{
add_device_randomness(unique_vm_id, size);
if (crng_ready()) {
crng_reseed(true);
pr_notice("crng reseeded due to virtual machine fork\n");
}
blocking_notifier_call_chain(&vmfork_chain, 0, NULL);
}
#if IS_MODULE(CONFIG_VMGENID)
EXPORT_SYMBOL_GPL(add_vmfork_randomness);
#endif
int register_random_vmfork_notifier(struct notifier_block *nb)
{
return blocking_notifier_chain_register(&vmfork_chain, nb);
}
EXPORT_SYMBOL_GPL(register_random_vmfork_notifier);
int unregister_random_vmfork_notifier(struct notifier_block *nb)
{
return blocking_notifier_chain_unregister(&vmfork_chain, nb);
}
EXPORT_SYMBOL_GPL(unregister_random_vmfork_notifier);
#endif
struct fast_pool {
random: defer fast pool mixing to worker On PREEMPT_RT, it's problematic to take spinlocks from hard irq handlers. We can fix this by deferring to a workqueue the dumping of the fast pool into the input pool. We accomplish this with some careful rules on fast_pool->count: - When it's incremented to >= 64, we schedule the work. - If the top bit is set, we never schedule the work, even if >= 64. - The worker is responsible for setting it back to 0 when it's done. There are two small issues around using workqueues for this purpose that we work around. The first issue is that mix_interrupt_randomness() might be migrated to another CPU during CPU hotplug. This issue is rectified by checking that it hasn't been migrated (after disabling irqs). If it has been migrated, then we set the count to zero, so that when the CPU comes online again, it can requeue the work. As part of this, we switch to using an atomic_t, so that the increment in the irq handler doesn't wipe out the zeroing if the CPU comes back online while this worker is running. The second issue is that, though relatively minor in effect, we probably want to make sure we get a consistent view of the pool onto the stack, in case it's interrupted by an irq while reading. To do this, we don't reenable irqs until after the copy. There are only 18 instructions between the cli and sti, so this is a pretty tiny window. Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Theodore Ts'o <tytso@mit.edu> Cc: Jonathan Neuschäfer <j.neuschaefer@gmx.net> Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Sultan Alsawaf <sultan@kerneltoast.com> Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-04 15:15:46 +00:00
struct work_struct mix;
random: use SipHash as interrupt entropy accumulator The current fast_mix() function is a piece of classic mailing list crypto, where it just sort of sprung up by an anonymous author without a lot of real analysis of what precisely it was accomplishing. As an ARX permutation alone, there are some easily searchable differential trails in it, and as a means of preventing malicious interrupts, it completely fails, since it xors new data into the entire state every time. It can't really be analyzed as a random permutation, because it clearly isn't, and it can't be analyzed as an interesting linear algebraic structure either, because it's also not that. There really is very little one can say about it in terms of entropy accumulation. It might diffuse bits, some of the time, maybe, we hope, I guess. But for the most part, it fails to accomplish anything concrete. As a reminder, the simple goal of add_interrupt_randomness() is to simply accumulate entropy until ~64 interrupts have elapsed, and then dump it into the main input pool, which uses a cryptographic hash. It would be nice to have something cryptographically strong in the interrupt handler itself, in case a malicious interrupt compromises a per-cpu fast pool within the 64 interrupts / 1 second window, and then inside of that same window somehow can control its return address and cycle counter, even if that's a bit far fetched. However, with a very CPU-limited budget, actually doing that remains an active research project (and perhaps there'll be something useful for Linux to come out of it). And while the abundance of caution would be nice, this isn't *currently* the security model, and we don't yet have a fast enough solution to make it our security model. Plus there's not exactly a pressing need to do that. (And for the avoidance of doubt, the actual cluster of 64 accumulated interrupts still gets dumped into our cryptographically secure input pool.) So, for now we are going to stick with the existing interrupt security model, which assumes that each cluster of 64 interrupt data samples is mostly non-malicious and not colluding with an infoleaker. With this as our goal, we have a few more choices, simply aiming to accumulate entropy, while discarding the least amount of it. We know from <https://eprint.iacr.org/2019/198> that random oracles, instantiated as computational hash functions, make good entropy accumulators and extractors, which is the justification for using BLAKE2s in the main input pool. As mentioned, we don't have that luxury here, but we also don't have the same security model requirements, because we're assuming that there aren't malicious inputs. A pseudorandom function instance can approximately behave like a random oracle, provided that the key is uniformly random. But since we're not concerned with malicious inputs, we can pick a fixed key, which is not secret, knowing that "nature" won't interact with a sufficiently chosen fixed key by accident. So we pick a PRF with a fixed initial key, and accumulate into it continuously, dumping the result every 64 interrupts into our cryptographically secure input pool. For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on 32-bit, which are already in use in the kernel's hsiphash family of functions and achieve the same performance as the function they replace. It would be nice to do two rounds, but we don't exactly have the CPU budget handy for that, and one round alone is already sufficient. As mentioned, we start with a fixed initial key (zeros is fine), and allow SipHash's symmetry breaking constants to turn that into a useful starting point. Also, since we're dumping the result (or half of it on 64-bit so as to tax our hash function the same amount on all platforms) into the cryptographically secure input pool, there's no point in finalizing SipHash's output, since it'll wind up being finalized by something much stronger. This means that all we need to do is use the ordinary round function word-by-word, as normal SipHash does. Simplified, the flow is as follows: Initialize: siphash_state_t state; siphash_init(&state, key={0, 0, 0, 0}); Update (accumulate) on interrupt: siphash_update(&state, interrupt_data_and_timing); Dump into input pool after 64 interrupts: blake2s_update(&input_pool, &state, sizeof(state) / 2); The result of all of this is that the security model is unchanged from before -- we assume non-malicious inputs -- yet we now implement that model with a stronger argument. I would like to emphasize, again, that the purpose of this commit is to improve the existing design, by making it analyzable, without changing any fundamental assumptions. There may well be value down the road in changing up the existing design, using something cryptographically strong, or simply using a ring buffer of samples rather than having a fast_mix() at all, or changing which and how much data we collect each interrupt so that we can use something linear, or a variety of other ideas. This commit does not invalidate the potential for those in the future. For example, in the future, if we're able to characterize the data we're collecting on each interrupt, we may be able to inch toward information theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s = ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good accumulators for 2-monotone distributions, which would apply to timestamp counters, like random_get_entropy() or jiffies, but would not apply to our current combination of the two values, or to the various function addresses and register values we mix in. Alternatively, <https://eprint.iacr.org/2021/1002> shows that max-period linear functions with no non-trivial invariant subspace make good extractors, used in the form `s = f(s) ^ x`. However, this only works if the input data is both identical and independent, and obviously a collection of address values and counters fails; so it goes with theoretical papers. Future directions here may involve trying to characterize more precisely what we actually need to collect in the interrupt handler, and building something specific around that. However, as mentioned, the morass of data we're gathering at the interrupt handler presently defies characterization, and so we use SipHash for now, which works well and performs well. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 13:58:44 +00:00
unsigned long pool[4];
unsigned long last;
unsigned int count;
u16 reg_idx;
};
random: use SipHash as interrupt entropy accumulator The current fast_mix() function is a piece of classic mailing list crypto, where it just sort of sprung up by an anonymous author without a lot of real analysis of what precisely it was accomplishing. As an ARX permutation alone, there are some easily searchable differential trails in it, and as a means of preventing malicious interrupts, it completely fails, since it xors new data into the entire state every time. It can't really be analyzed as a random permutation, because it clearly isn't, and it can't be analyzed as an interesting linear algebraic structure either, because it's also not that. There really is very little one can say about it in terms of entropy accumulation. It might diffuse bits, some of the time, maybe, we hope, I guess. But for the most part, it fails to accomplish anything concrete. As a reminder, the simple goal of add_interrupt_randomness() is to simply accumulate entropy until ~64 interrupts have elapsed, and then dump it into the main input pool, which uses a cryptographic hash. It would be nice to have something cryptographically strong in the interrupt handler itself, in case a malicious interrupt compromises a per-cpu fast pool within the 64 interrupts / 1 second window, and then inside of that same window somehow can control its return address and cycle counter, even if that's a bit far fetched. However, with a very CPU-limited budget, actually doing that remains an active research project (and perhaps there'll be something useful for Linux to come out of it). And while the abundance of caution would be nice, this isn't *currently* the security model, and we don't yet have a fast enough solution to make it our security model. Plus there's not exactly a pressing need to do that. (And for the avoidance of doubt, the actual cluster of 64 accumulated interrupts still gets dumped into our cryptographically secure input pool.) So, for now we are going to stick with the existing interrupt security model, which assumes that each cluster of 64 interrupt data samples is mostly non-malicious and not colluding with an infoleaker. With this as our goal, we have a few more choices, simply aiming to accumulate entropy, while discarding the least amount of it. We know from <https://eprint.iacr.org/2019/198> that random oracles, instantiated as computational hash functions, make good entropy accumulators and extractors, which is the justification for using BLAKE2s in the main input pool. As mentioned, we don't have that luxury here, but we also don't have the same security model requirements, because we're assuming that there aren't malicious inputs. A pseudorandom function instance can approximately behave like a random oracle, provided that the key is uniformly random. But since we're not concerned with malicious inputs, we can pick a fixed key, which is not secret, knowing that "nature" won't interact with a sufficiently chosen fixed key by accident. So we pick a PRF with a fixed initial key, and accumulate into it continuously, dumping the result every 64 interrupts into our cryptographically secure input pool. For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on 32-bit, which are already in use in the kernel's hsiphash family of functions and achieve the same performance as the function they replace. It would be nice to do two rounds, but we don't exactly have the CPU budget handy for that, and one round alone is already sufficient. As mentioned, we start with a fixed initial key (zeros is fine), and allow SipHash's symmetry breaking constants to turn that into a useful starting point. Also, since we're dumping the result (or half of it on 64-bit so as to tax our hash function the same amount on all platforms) into the cryptographically secure input pool, there's no point in finalizing SipHash's output, since it'll wind up being finalized by something much stronger. This means that all we need to do is use the ordinary round function word-by-word, as normal SipHash does. Simplified, the flow is as follows: Initialize: siphash_state_t state; siphash_init(&state, key={0, 0, 0, 0}); Update (accumulate) on interrupt: siphash_update(&state, interrupt_data_and_timing); Dump into input pool after 64 interrupts: blake2s_update(&input_pool, &state, sizeof(state) / 2); The result of all of this is that the security model is unchanged from before -- we assume non-malicious inputs -- yet we now implement that model with a stronger argument. I would like to emphasize, again, that the purpose of this commit is to improve the existing design, by making it analyzable, without changing any fundamental assumptions. There may well be value down the road in changing up the existing design, using something cryptographically strong, or simply using a ring buffer of samples rather than having a fast_mix() at all, or changing which and how much data we collect each interrupt so that we can use something linear, or a variety of other ideas. This commit does not invalidate the potential for those in the future. For example, in the future, if we're able to characterize the data we're collecting on each interrupt, we may be able to inch toward information theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s = ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good accumulators for 2-monotone distributions, which would apply to timestamp counters, like random_get_entropy() or jiffies, but would not apply to our current combination of the two values, or to the various function addresses and register values we mix in. Alternatively, <https://eprint.iacr.org/2021/1002> shows that max-period linear functions with no non-trivial invariant subspace make good extractors, used in the form `s = f(s) ^ x`. However, this only works if the input data is both identical and independent, and obviously a collection of address values and counters fails; so it goes with theoretical papers. Future directions here may involve trying to characterize more precisely what we actually need to collect in the interrupt handler, and building something specific around that. However, as mentioned, the morass of data we're gathering at the interrupt handler presently defies characterization, and so we use SipHash for now, which works well and performs well. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 13:58:44 +00:00
static DEFINE_PER_CPU(struct fast_pool, irq_randomness) = {
#ifdef CONFIG_64BIT
/* SipHash constants */
.pool = { 0x736f6d6570736575UL, 0x646f72616e646f6dUL,
0x6c7967656e657261UL, 0x7465646279746573UL }
#else
/* HalfSipHash constants */
.pool = { 0, 0, 0x6c796765U, 0x74656462U }
#endif
};
/*
random: use SipHash as interrupt entropy accumulator The current fast_mix() function is a piece of classic mailing list crypto, where it just sort of sprung up by an anonymous author without a lot of real analysis of what precisely it was accomplishing. As an ARX permutation alone, there are some easily searchable differential trails in it, and as a means of preventing malicious interrupts, it completely fails, since it xors new data into the entire state every time. It can't really be analyzed as a random permutation, because it clearly isn't, and it can't be analyzed as an interesting linear algebraic structure either, because it's also not that. There really is very little one can say about it in terms of entropy accumulation. It might diffuse bits, some of the time, maybe, we hope, I guess. But for the most part, it fails to accomplish anything concrete. As a reminder, the simple goal of add_interrupt_randomness() is to simply accumulate entropy until ~64 interrupts have elapsed, and then dump it into the main input pool, which uses a cryptographic hash. It would be nice to have something cryptographically strong in the interrupt handler itself, in case a malicious interrupt compromises a per-cpu fast pool within the 64 interrupts / 1 second window, and then inside of that same window somehow can control its return address and cycle counter, even if that's a bit far fetched. However, with a very CPU-limited budget, actually doing that remains an active research project (and perhaps there'll be something useful for Linux to come out of it). And while the abundance of caution would be nice, this isn't *currently* the security model, and we don't yet have a fast enough solution to make it our security model. Plus there's not exactly a pressing need to do that. (And for the avoidance of doubt, the actual cluster of 64 accumulated interrupts still gets dumped into our cryptographically secure input pool.) So, for now we are going to stick with the existing interrupt security model, which assumes that each cluster of 64 interrupt data samples is mostly non-malicious and not colluding with an infoleaker. With this as our goal, we have a few more choices, simply aiming to accumulate entropy, while discarding the least amount of it. We know from <https://eprint.iacr.org/2019/198> that random oracles, instantiated as computational hash functions, make good entropy accumulators and extractors, which is the justification for using BLAKE2s in the main input pool. As mentioned, we don't have that luxury here, but we also don't have the same security model requirements, because we're assuming that there aren't malicious inputs. A pseudorandom function instance can approximately behave like a random oracle, provided that the key is uniformly random. But since we're not concerned with malicious inputs, we can pick a fixed key, which is not secret, knowing that "nature" won't interact with a sufficiently chosen fixed key by accident. So we pick a PRF with a fixed initial key, and accumulate into it continuously, dumping the result every 64 interrupts into our cryptographically secure input pool. For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on 32-bit, which are already in use in the kernel's hsiphash family of functions and achieve the same performance as the function they replace. It would be nice to do two rounds, but we don't exactly have the CPU budget handy for that, and one round alone is already sufficient. As mentioned, we start with a fixed initial key (zeros is fine), and allow SipHash's symmetry breaking constants to turn that into a useful starting point. Also, since we're dumping the result (or half of it on 64-bit so as to tax our hash function the same amount on all platforms) into the cryptographically secure input pool, there's no point in finalizing SipHash's output, since it'll wind up being finalized by something much stronger. This means that all we need to do is use the ordinary round function word-by-word, as normal SipHash does. Simplified, the flow is as follows: Initialize: siphash_state_t state; siphash_init(&state, key={0, 0, 0, 0}); Update (accumulate) on interrupt: siphash_update(&state, interrupt_data_and_timing); Dump into input pool after 64 interrupts: blake2s_update(&input_pool, &state, sizeof(state) / 2); The result of all of this is that the security model is unchanged from before -- we assume non-malicious inputs -- yet we now implement that model with a stronger argument. I would like to emphasize, again, that the purpose of this commit is to improve the existing design, by making it analyzable, without changing any fundamental assumptions. There may well be value down the road in changing up the existing design, using something cryptographically strong, or simply using a ring buffer of samples rather than having a fast_mix() at all, or changing which and how much data we collect each interrupt so that we can use something linear, or a variety of other ideas. This commit does not invalidate the potential for those in the future. For example, in the future, if we're able to characterize the data we're collecting on each interrupt, we may be able to inch toward information theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s = ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good accumulators for 2-monotone distributions, which would apply to timestamp counters, like random_get_entropy() or jiffies, but would not apply to our current combination of the two values, or to the various function addresses and register values we mix in. Alternatively, <https://eprint.iacr.org/2021/1002> shows that max-period linear functions with no non-trivial invariant subspace make good extractors, used in the form `s = f(s) ^ x`. However, this only works if the input data is both identical and independent, and obviously a collection of address values and counters fails; so it goes with theoretical papers. Future directions here may involve trying to characterize more precisely what we actually need to collect in the interrupt handler, and building something specific around that. However, as mentioned, the morass of data we're gathering at the interrupt handler presently defies characterization, and so we use SipHash for now, which works well and performs well. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 13:58:44 +00:00
* This is [Half]SipHash-1-x, starting from an empty key. Because
* the key is fixed, it assumes that its inputs are non-malicious,
* and therefore this has no security on its own. s represents the
* 128 or 256-bit SipHash state, while v represents a 128-bit input.
*/
random: use SipHash as interrupt entropy accumulator The current fast_mix() function is a piece of classic mailing list crypto, where it just sort of sprung up by an anonymous author without a lot of real analysis of what precisely it was accomplishing. As an ARX permutation alone, there are some easily searchable differential trails in it, and as a means of preventing malicious interrupts, it completely fails, since it xors new data into the entire state every time. It can't really be analyzed as a random permutation, because it clearly isn't, and it can't be analyzed as an interesting linear algebraic structure either, because it's also not that. There really is very little one can say about it in terms of entropy accumulation. It might diffuse bits, some of the time, maybe, we hope, I guess. But for the most part, it fails to accomplish anything concrete. As a reminder, the simple goal of add_interrupt_randomness() is to simply accumulate entropy until ~64 interrupts have elapsed, and then dump it into the main input pool, which uses a cryptographic hash. It would be nice to have something cryptographically strong in the interrupt handler itself, in case a malicious interrupt compromises a per-cpu fast pool within the 64 interrupts / 1 second window, and then inside of that same window somehow can control its return address and cycle counter, even if that's a bit far fetched. However, with a very CPU-limited budget, actually doing that remains an active research project (and perhaps there'll be something useful for Linux to come out of it). And while the abundance of caution would be nice, this isn't *currently* the security model, and we don't yet have a fast enough solution to make it our security model. Plus there's not exactly a pressing need to do that. (And for the avoidance of doubt, the actual cluster of 64 accumulated interrupts still gets dumped into our cryptographically secure input pool.) So, for now we are going to stick with the existing interrupt security model, which assumes that each cluster of 64 interrupt data samples is mostly non-malicious and not colluding with an infoleaker. With this as our goal, we have a few more choices, simply aiming to accumulate entropy, while discarding the least amount of it. We know from <https://eprint.iacr.org/2019/198> that random oracles, instantiated as computational hash functions, make good entropy accumulators and extractors, which is the justification for using BLAKE2s in the main input pool. As mentioned, we don't have that luxury here, but we also don't have the same security model requirements, because we're assuming that there aren't malicious inputs. A pseudorandom function instance can approximately behave like a random oracle, provided that the key is uniformly random. But since we're not concerned with malicious inputs, we can pick a fixed key, which is not secret, knowing that "nature" won't interact with a sufficiently chosen fixed key by accident. So we pick a PRF with a fixed initial key, and accumulate into it continuously, dumping the result every 64 interrupts into our cryptographically secure input pool. For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on 32-bit, which are already in use in the kernel's hsiphash family of functions and achieve the same performance as the function they replace. It would be nice to do two rounds, but we don't exactly have the CPU budget handy for that, and one round alone is already sufficient. As mentioned, we start with a fixed initial key (zeros is fine), and allow SipHash's symmetry breaking constants to turn that into a useful starting point. Also, since we're dumping the result (or half of it on 64-bit so as to tax our hash function the same amount on all platforms) into the cryptographically secure input pool, there's no point in finalizing SipHash's output, since it'll wind up being finalized by something much stronger. This means that all we need to do is use the ordinary round function word-by-word, as normal SipHash does. Simplified, the flow is as follows: Initialize: siphash_state_t state; siphash_init(&state, key={0, 0, 0, 0}); Update (accumulate) on interrupt: siphash_update(&state, interrupt_data_and_timing); Dump into input pool after 64 interrupts: blake2s_update(&input_pool, &state, sizeof(state) / 2); The result of all of this is that the security model is unchanged from before -- we assume non-malicious inputs -- yet we now implement that model with a stronger argument. I would like to emphasize, again, that the purpose of this commit is to improve the existing design, by making it analyzable, without changing any fundamental assumptions. There may well be value down the road in changing up the existing design, using something cryptographically strong, or simply using a ring buffer of samples rather than having a fast_mix() at all, or changing which and how much data we collect each interrupt so that we can use something linear, or a variety of other ideas. This commit does not invalidate the potential for those in the future. For example, in the future, if we're able to characterize the data we're collecting on each interrupt, we may be able to inch toward information theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s = ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good accumulators for 2-monotone distributions, which would apply to timestamp counters, like random_get_entropy() or jiffies, but would not apply to our current combination of the two values, or to the various function addresses and register values we mix in. Alternatively, <https://eprint.iacr.org/2021/1002> shows that max-period linear functions with no non-trivial invariant subspace make good extractors, used in the form `s = f(s) ^ x`. However, this only works if the input data is both identical and independent, and obviously a collection of address values and counters fails; so it goes with theoretical papers. Future directions here may involve trying to characterize more precisely what we actually need to collect in the interrupt handler, and building something specific around that. However, as mentioned, the morass of data we're gathering at the interrupt handler presently defies characterization, and so we use SipHash for now, which works well and performs well. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 13:58:44 +00:00
static void fast_mix(unsigned long s[4], const unsigned long *v)
{
random: use SipHash as interrupt entropy accumulator The current fast_mix() function is a piece of classic mailing list crypto, where it just sort of sprung up by an anonymous author without a lot of real analysis of what precisely it was accomplishing. As an ARX permutation alone, there are some easily searchable differential trails in it, and as a means of preventing malicious interrupts, it completely fails, since it xors new data into the entire state every time. It can't really be analyzed as a random permutation, because it clearly isn't, and it can't be analyzed as an interesting linear algebraic structure either, because it's also not that. There really is very little one can say about it in terms of entropy accumulation. It might diffuse bits, some of the time, maybe, we hope, I guess. But for the most part, it fails to accomplish anything concrete. As a reminder, the simple goal of add_interrupt_randomness() is to simply accumulate entropy until ~64 interrupts have elapsed, and then dump it into the main input pool, which uses a cryptographic hash. It would be nice to have something cryptographically strong in the interrupt handler itself, in case a malicious interrupt compromises a per-cpu fast pool within the 64 interrupts / 1 second window, and then inside of that same window somehow can control its return address and cycle counter, even if that's a bit far fetched. However, with a very CPU-limited budget, actually doing that remains an active research project (and perhaps there'll be something useful for Linux to come out of it). And while the abundance of caution would be nice, this isn't *currently* the security model, and we don't yet have a fast enough solution to make it our security model. Plus there's not exactly a pressing need to do that. (And for the avoidance of doubt, the actual cluster of 64 accumulated interrupts still gets dumped into our cryptographically secure input pool.) So, for now we are going to stick with the existing interrupt security model, which assumes that each cluster of 64 interrupt data samples is mostly non-malicious and not colluding with an infoleaker. With this as our goal, we have a few more choices, simply aiming to accumulate entropy, while discarding the least amount of it. We know from <https://eprint.iacr.org/2019/198> that random oracles, instantiated as computational hash functions, make good entropy accumulators and extractors, which is the justification for using BLAKE2s in the main input pool. As mentioned, we don't have that luxury here, but we also don't have the same security model requirements, because we're assuming that there aren't malicious inputs. A pseudorandom function instance can approximately behave like a random oracle, provided that the key is uniformly random. But since we're not concerned with malicious inputs, we can pick a fixed key, which is not secret, knowing that "nature" won't interact with a sufficiently chosen fixed key by accident. So we pick a PRF with a fixed initial key, and accumulate into it continuously, dumping the result every 64 interrupts into our cryptographically secure input pool. For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on 32-bit, which are already in use in the kernel's hsiphash family of functions and achieve the same performance as the function they replace. It would be nice to do two rounds, but we don't exactly have the CPU budget handy for that, and one round alone is already sufficient. As mentioned, we start with a fixed initial key (zeros is fine), and allow SipHash's symmetry breaking constants to turn that into a useful starting point. Also, since we're dumping the result (or half of it on 64-bit so as to tax our hash function the same amount on all platforms) into the cryptographically secure input pool, there's no point in finalizing SipHash's output, since it'll wind up being finalized by something much stronger. This means that all we need to do is use the ordinary round function word-by-word, as normal SipHash does. Simplified, the flow is as follows: Initialize: siphash_state_t state; siphash_init(&state, key={0, 0, 0, 0}); Update (accumulate) on interrupt: siphash_update(&state, interrupt_data_and_timing); Dump into input pool after 64 interrupts: blake2s_update(&input_pool, &state, sizeof(state) / 2); The result of all of this is that the security model is unchanged from before -- we assume non-malicious inputs -- yet we now implement that model with a stronger argument. I would like to emphasize, again, that the purpose of this commit is to improve the existing design, by making it analyzable, without changing any fundamental assumptions. There may well be value down the road in changing up the existing design, using something cryptographically strong, or simply using a ring buffer of samples rather than having a fast_mix() at all, or changing which and how much data we collect each interrupt so that we can use something linear, or a variety of other ideas. This commit does not invalidate the potential for those in the future. For example, in the future, if we're able to characterize the data we're collecting on each interrupt, we may be able to inch toward information theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s = ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good accumulators for 2-monotone distributions, which would apply to timestamp counters, like random_get_entropy() or jiffies, but would not apply to our current combination of the two values, or to the various function addresses and register values we mix in. Alternatively, <https://eprint.iacr.org/2021/1002> shows that max-period linear functions with no non-trivial invariant subspace make good extractors, used in the form `s = f(s) ^ x`. However, this only works if the input data is both identical and independent, and obviously a collection of address values and counters fails; so it goes with theoretical papers. Future directions here may involve trying to characterize more precisely what we actually need to collect in the interrupt handler, and building something specific around that. However, as mentioned, the morass of data we're gathering at the interrupt handler presently defies characterization, and so we use SipHash for now, which works well and performs well. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 13:58:44 +00:00
size_t i;
random: use SipHash as interrupt entropy accumulator The current fast_mix() function is a piece of classic mailing list crypto, where it just sort of sprung up by an anonymous author without a lot of real analysis of what precisely it was accomplishing. As an ARX permutation alone, there are some easily searchable differential trails in it, and as a means of preventing malicious interrupts, it completely fails, since it xors new data into the entire state every time. It can't really be analyzed as a random permutation, because it clearly isn't, and it can't be analyzed as an interesting linear algebraic structure either, because it's also not that. There really is very little one can say about it in terms of entropy accumulation. It might diffuse bits, some of the time, maybe, we hope, I guess. But for the most part, it fails to accomplish anything concrete. As a reminder, the simple goal of add_interrupt_randomness() is to simply accumulate entropy until ~64 interrupts have elapsed, and then dump it into the main input pool, which uses a cryptographic hash. It would be nice to have something cryptographically strong in the interrupt handler itself, in case a malicious interrupt compromises a per-cpu fast pool within the 64 interrupts / 1 second window, and then inside of that same window somehow can control its return address and cycle counter, even if that's a bit far fetched. However, with a very CPU-limited budget, actually doing that remains an active research project (and perhaps there'll be something useful for Linux to come out of it). And while the abundance of caution would be nice, this isn't *currently* the security model, and we don't yet have a fast enough solution to make it our security model. Plus there's not exactly a pressing need to do that. (And for the avoidance of doubt, the actual cluster of 64 accumulated interrupts still gets dumped into our cryptographically secure input pool.) So, for now we are going to stick with the existing interrupt security model, which assumes that each cluster of 64 interrupt data samples is mostly non-malicious and not colluding with an infoleaker. With this as our goal, we have a few more choices, simply aiming to accumulate entropy, while discarding the least amount of it. We know from <https://eprint.iacr.org/2019/198> that random oracles, instantiated as computational hash functions, make good entropy accumulators and extractors, which is the justification for using BLAKE2s in the main input pool. As mentioned, we don't have that luxury here, but we also don't have the same security model requirements, because we're assuming that there aren't malicious inputs. A pseudorandom function instance can approximately behave like a random oracle, provided that the key is uniformly random. But since we're not concerned with malicious inputs, we can pick a fixed key, which is not secret, knowing that "nature" won't interact with a sufficiently chosen fixed key by accident. So we pick a PRF with a fixed initial key, and accumulate into it continuously, dumping the result every 64 interrupts into our cryptographically secure input pool. For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on 32-bit, which are already in use in the kernel's hsiphash family of functions and achieve the same performance as the function they replace. It would be nice to do two rounds, but we don't exactly have the CPU budget handy for that, and one round alone is already sufficient. As mentioned, we start with a fixed initial key (zeros is fine), and allow SipHash's symmetry breaking constants to turn that into a useful starting point. Also, since we're dumping the result (or half of it on 64-bit so as to tax our hash function the same amount on all platforms) into the cryptographically secure input pool, there's no point in finalizing SipHash's output, since it'll wind up being finalized by something much stronger. This means that all we need to do is use the ordinary round function word-by-word, as normal SipHash does. Simplified, the flow is as follows: Initialize: siphash_state_t state; siphash_init(&state, key={0, 0, 0, 0}); Update (accumulate) on interrupt: siphash_update(&state, interrupt_data_and_timing); Dump into input pool after 64 interrupts: blake2s_update(&input_pool, &state, sizeof(state) / 2); The result of all of this is that the security model is unchanged from before -- we assume non-malicious inputs -- yet we now implement that model with a stronger argument. I would like to emphasize, again, that the purpose of this commit is to improve the existing design, by making it analyzable, without changing any fundamental assumptions. There may well be value down the road in changing up the existing design, using something cryptographically strong, or simply using a ring buffer of samples rather than having a fast_mix() at all, or changing which and how much data we collect each interrupt so that we can use something linear, or a variety of other ideas. This commit does not invalidate the potential for those in the future. For example, in the future, if we're able to characterize the data we're collecting on each interrupt, we may be able to inch toward information theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s = ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good accumulators for 2-monotone distributions, which would apply to timestamp counters, like random_get_entropy() or jiffies, but would not apply to our current combination of the two values, or to the various function addresses and register values we mix in. Alternatively, <https://eprint.iacr.org/2021/1002> shows that max-period linear functions with no non-trivial invariant subspace make good extractors, used in the form `s = f(s) ^ x`. However, this only works if the input data is both identical and independent, and obviously a collection of address values and counters fails; so it goes with theoretical papers. Future directions here may involve trying to characterize more precisely what we actually need to collect in the interrupt handler, and building something specific around that. However, as mentioned, the morass of data we're gathering at the interrupt handler presently defies characterization, and so we use SipHash for now, which works well and performs well. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 13:58:44 +00:00
for (i = 0; i < 16 / sizeof(long); ++i) {
s[3] ^= v[i];
#ifdef CONFIG_64BIT
s[0] += s[1]; s[1] = rol64(s[1], 13); s[1] ^= s[0]; s[0] = rol64(s[0], 32);
s[2] += s[3]; s[3] = rol64(s[3], 16); s[3] ^= s[2];
s[0] += s[3]; s[3] = rol64(s[3], 21); s[3] ^= s[0];
s[2] += s[1]; s[1] = rol64(s[1], 17); s[1] ^= s[2]; s[2] = rol64(s[2], 32);
#else
s[0] += s[1]; s[1] = rol32(s[1], 5); s[1] ^= s[0]; s[0] = rol32(s[0], 16);
s[2] += s[3]; s[3] = rol32(s[3], 8); s[3] ^= s[2];
s[0] += s[3]; s[3] = rol32(s[3], 7); s[3] ^= s[0];
s[2] += s[1]; s[1] = rol32(s[1], 13); s[1] ^= s[2]; s[2] = rol32(s[2], 16);
#endif
s[0] ^= v[i];
}
}
#ifdef CONFIG_SMP
/*
* This function is called when the CPU has just come online, with
* entry CPUHP_AP_RANDOM_ONLINE, just after CPUHP_AP_WORKQUEUE_ONLINE.
*/
int random_online_cpu(unsigned int cpu)
{
/*
* During CPU shutdown and before CPU onlining, add_interrupt_
* randomness() may schedule mix_interrupt_randomness(), and
* set the MIX_INFLIGHT flag. However, because the worker can
* be scheduled on a different CPU during this period, that
* flag will never be cleared. For that reason, we zero out
* the flag here, which runs just after workqueues are onlined
* for the CPU again. This also has the effect of setting the
* irq randomness count to zero so that new accumulated irqs
* are fresh.
*/
per_cpu_ptr(&irq_randomness, cpu)->count = 0;
return 0;
}
#endif
static unsigned long get_reg(struct fast_pool *f, struct pt_regs *regs)
{
unsigned long *ptr = (unsigned long *)regs;
unsigned int idx;
if (regs == NULL)
return 0;
idx = READ_ONCE(f->reg_idx);
if (idx >= sizeof(struct pt_regs) / sizeof(unsigned long))
idx = 0;
ptr += idx++;
WRITE_ONCE(f->reg_idx, idx);
return *ptr;
}
random: defer fast pool mixing to worker On PREEMPT_RT, it's problematic to take spinlocks from hard irq handlers. We can fix this by deferring to a workqueue the dumping of the fast pool into the input pool. We accomplish this with some careful rules on fast_pool->count: - When it's incremented to >= 64, we schedule the work. - If the top bit is set, we never schedule the work, even if >= 64. - The worker is responsible for setting it back to 0 when it's done. There are two small issues around using workqueues for this purpose that we work around. The first issue is that mix_interrupt_randomness() might be migrated to another CPU during CPU hotplug. This issue is rectified by checking that it hasn't been migrated (after disabling irqs). If it has been migrated, then we set the count to zero, so that when the CPU comes online again, it can requeue the work. As part of this, we switch to using an atomic_t, so that the increment in the irq handler doesn't wipe out the zeroing if the CPU comes back online while this worker is running. The second issue is that, though relatively minor in effect, we probably want to make sure we get a consistent view of the pool onto the stack, in case it's interrupted by an irq while reading. To do this, we don't reenable irqs until after the copy. There are only 18 instructions between the cli and sti, so this is a pretty tiny window. Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Theodore Ts'o <tytso@mit.edu> Cc: Jonathan Neuschäfer <j.neuschaefer@gmx.net> Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Sultan Alsawaf <sultan@kerneltoast.com> Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-04 15:15:46 +00:00
static void mix_interrupt_randomness(struct work_struct *work)
{
struct fast_pool *fast_pool = container_of(work, struct fast_pool, mix);
random: use SipHash as interrupt entropy accumulator The current fast_mix() function is a piece of classic mailing list crypto, where it just sort of sprung up by an anonymous author without a lot of real analysis of what precisely it was accomplishing. As an ARX permutation alone, there are some easily searchable differential trails in it, and as a means of preventing malicious interrupts, it completely fails, since it xors new data into the entire state every time. It can't really be analyzed as a random permutation, because it clearly isn't, and it can't be analyzed as an interesting linear algebraic structure either, because it's also not that. There really is very little one can say about it in terms of entropy accumulation. It might diffuse bits, some of the time, maybe, we hope, I guess. But for the most part, it fails to accomplish anything concrete. As a reminder, the simple goal of add_interrupt_randomness() is to simply accumulate entropy until ~64 interrupts have elapsed, and then dump it into the main input pool, which uses a cryptographic hash. It would be nice to have something cryptographically strong in the interrupt handler itself, in case a malicious interrupt compromises a per-cpu fast pool within the 64 interrupts / 1 second window, and then inside of that same window somehow can control its return address and cycle counter, even if that's a bit far fetched. However, with a very CPU-limited budget, actually doing that remains an active research project (and perhaps there'll be something useful for Linux to come out of it). And while the abundance of caution would be nice, this isn't *currently* the security model, and we don't yet have a fast enough solution to make it our security model. Plus there's not exactly a pressing need to do that. (And for the avoidance of doubt, the actual cluster of 64 accumulated interrupts still gets dumped into our cryptographically secure input pool.) So, for now we are going to stick with the existing interrupt security model, which assumes that each cluster of 64 interrupt data samples is mostly non-malicious and not colluding with an infoleaker. With this as our goal, we have a few more choices, simply aiming to accumulate entropy, while discarding the least amount of it. We know from <https://eprint.iacr.org/2019/198> that random oracles, instantiated as computational hash functions, make good entropy accumulators and extractors, which is the justification for using BLAKE2s in the main input pool. As mentioned, we don't have that luxury here, but we also don't have the same security model requirements, because we're assuming that there aren't malicious inputs. A pseudorandom function instance can approximately behave like a random oracle, provided that the key is uniformly random. But since we're not concerned with malicious inputs, we can pick a fixed key, which is not secret, knowing that "nature" won't interact with a sufficiently chosen fixed key by accident. So we pick a PRF with a fixed initial key, and accumulate into it continuously, dumping the result every 64 interrupts into our cryptographically secure input pool. For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on 32-bit, which are already in use in the kernel's hsiphash family of functions and achieve the same performance as the function they replace. It would be nice to do two rounds, but we don't exactly have the CPU budget handy for that, and one round alone is already sufficient. As mentioned, we start with a fixed initial key (zeros is fine), and allow SipHash's symmetry breaking constants to turn that into a useful starting point. Also, since we're dumping the result (or half of it on 64-bit so as to tax our hash function the same amount on all platforms) into the cryptographically secure input pool, there's no point in finalizing SipHash's output, since it'll wind up being finalized by something much stronger. This means that all we need to do is use the ordinary round function word-by-word, as normal SipHash does. Simplified, the flow is as follows: Initialize: siphash_state_t state; siphash_init(&state, key={0, 0, 0, 0}); Update (accumulate) on interrupt: siphash_update(&state, interrupt_data_and_timing); Dump into input pool after 64 interrupts: blake2s_update(&input_pool, &state, sizeof(state) / 2); The result of all of this is that the security model is unchanged from before -- we assume non-malicious inputs -- yet we now implement that model with a stronger argument. I would like to emphasize, again, that the purpose of this commit is to improve the existing design, by making it analyzable, without changing any fundamental assumptions. There may well be value down the road in changing up the existing design, using something cryptographically strong, or simply using a ring buffer of samples rather than having a fast_mix() at all, or changing which and how much data we collect each interrupt so that we can use something linear, or a variety of other ideas. This commit does not invalidate the potential for those in the future. For example, in the future, if we're able to characterize the data we're collecting on each interrupt, we may be able to inch toward information theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s = ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good accumulators for 2-monotone distributions, which would apply to timestamp counters, like random_get_entropy() or jiffies, but would not apply to our current combination of the two values, or to the various function addresses and register values we mix in. Alternatively, <https://eprint.iacr.org/2021/1002> shows that max-period linear functions with no non-trivial invariant subspace make good extractors, used in the form `s = f(s) ^ x`. However, this only works if the input data is both identical and independent, and obviously a collection of address values and counters fails; so it goes with theoretical papers. Future directions here may involve trying to characterize more precisely what we actually need to collect in the interrupt handler, and building something specific around that. However, as mentioned, the morass of data we're gathering at the interrupt handler presently defies characterization, and so we use SipHash for now, which works well and performs well. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 13:58:44 +00:00
/*
* The size of the copied stack pool is explicitly 16 bytes so that we
* tax mix_pool_byte()'s compression function the same amount on all
* platforms. This means on 64-bit we copy half the pool into this,
* while on 32-bit we copy all of it. The entropy is supposed to be
* sufficiently dispersed between bits that in the sponge-like
* half case, on average we don't wind up "losing" some.
*/
u8 pool[16];
random: defer fast pool mixing to worker On PREEMPT_RT, it's problematic to take spinlocks from hard irq handlers. We can fix this by deferring to a workqueue the dumping of the fast pool into the input pool. We accomplish this with some careful rules on fast_pool->count: - When it's incremented to >= 64, we schedule the work. - If the top bit is set, we never schedule the work, even if >= 64. - The worker is responsible for setting it back to 0 when it's done. There are two small issues around using workqueues for this purpose that we work around. The first issue is that mix_interrupt_randomness() might be migrated to another CPU during CPU hotplug. This issue is rectified by checking that it hasn't been migrated (after disabling irqs). If it has been migrated, then we set the count to zero, so that when the CPU comes online again, it can requeue the work. As part of this, we switch to using an atomic_t, so that the increment in the irq handler doesn't wipe out the zeroing if the CPU comes back online while this worker is running. The second issue is that, though relatively minor in effect, we probably want to make sure we get a consistent view of the pool onto the stack, in case it's interrupted by an irq while reading. To do this, we don't reenable irqs until after the copy. There are only 18 instructions between the cli and sti, so this is a pretty tiny window. Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Theodore Ts'o <tytso@mit.edu> Cc: Jonathan Neuschäfer <j.neuschaefer@gmx.net> Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Sultan Alsawaf <sultan@kerneltoast.com> Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-04 15:15:46 +00:00
/* Check to see if we're running on the wrong CPU due to hotplug. */
local_irq_disable();
if (fast_pool != this_cpu_ptr(&irq_randomness)) {
local_irq_enable();
return;
}
/*
* Copy the pool to the stack so that the mixer always has a
* consistent view, before we reenable irqs again.
*/
random: use SipHash as interrupt entropy accumulator The current fast_mix() function is a piece of classic mailing list crypto, where it just sort of sprung up by an anonymous author without a lot of real analysis of what precisely it was accomplishing. As an ARX permutation alone, there are some easily searchable differential trails in it, and as a means of preventing malicious interrupts, it completely fails, since it xors new data into the entire state every time. It can't really be analyzed as a random permutation, because it clearly isn't, and it can't be analyzed as an interesting linear algebraic structure either, because it's also not that. There really is very little one can say about it in terms of entropy accumulation. It might diffuse bits, some of the time, maybe, we hope, I guess. But for the most part, it fails to accomplish anything concrete. As a reminder, the simple goal of add_interrupt_randomness() is to simply accumulate entropy until ~64 interrupts have elapsed, and then dump it into the main input pool, which uses a cryptographic hash. It would be nice to have something cryptographically strong in the interrupt handler itself, in case a malicious interrupt compromises a per-cpu fast pool within the 64 interrupts / 1 second window, and then inside of that same window somehow can control its return address and cycle counter, even if that's a bit far fetched. However, with a very CPU-limited budget, actually doing that remains an active research project (and perhaps there'll be something useful for Linux to come out of it). And while the abundance of caution would be nice, this isn't *currently* the security model, and we don't yet have a fast enough solution to make it our security model. Plus there's not exactly a pressing need to do that. (And for the avoidance of doubt, the actual cluster of 64 accumulated interrupts still gets dumped into our cryptographically secure input pool.) So, for now we are going to stick with the existing interrupt security model, which assumes that each cluster of 64 interrupt data samples is mostly non-malicious and not colluding with an infoleaker. With this as our goal, we have a few more choices, simply aiming to accumulate entropy, while discarding the least amount of it. We know from <https://eprint.iacr.org/2019/198> that random oracles, instantiated as computational hash functions, make good entropy accumulators and extractors, which is the justification for using BLAKE2s in the main input pool. As mentioned, we don't have that luxury here, but we also don't have the same security model requirements, because we're assuming that there aren't malicious inputs. A pseudorandom function instance can approximately behave like a random oracle, provided that the key is uniformly random. But since we're not concerned with malicious inputs, we can pick a fixed key, which is not secret, knowing that "nature" won't interact with a sufficiently chosen fixed key by accident. So we pick a PRF with a fixed initial key, and accumulate into it continuously, dumping the result every 64 interrupts into our cryptographically secure input pool. For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on 32-bit, which are already in use in the kernel's hsiphash family of functions and achieve the same performance as the function they replace. It would be nice to do two rounds, but we don't exactly have the CPU budget handy for that, and one round alone is already sufficient. As mentioned, we start with a fixed initial key (zeros is fine), and allow SipHash's symmetry breaking constants to turn that into a useful starting point. Also, since we're dumping the result (or half of it on 64-bit so as to tax our hash function the same amount on all platforms) into the cryptographically secure input pool, there's no point in finalizing SipHash's output, since it'll wind up being finalized by something much stronger. This means that all we need to do is use the ordinary round function word-by-word, as normal SipHash does. Simplified, the flow is as follows: Initialize: siphash_state_t state; siphash_init(&state, key={0, 0, 0, 0}); Update (accumulate) on interrupt: siphash_update(&state, interrupt_data_and_timing); Dump into input pool after 64 interrupts: blake2s_update(&input_pool, &state, sizeof(state) / 2); The result of all of this is that the security model is unchanged from before -- we assume non-malicious inputs -- yet we now implement that model with a stronger argument. I would like to emphasize, again, that the purpose of this commit is to improve the existing design, by making it analyzable, without changing any fundamental assumptions. There may well be value down the road in changing up the existing design, using something cryptographically strong, or simply using a ring buffer of samples rather than having a fast_mix() at all, or changing which and how much data we collect each interrupt so that we can use something linear, or a variety of other ideas. This commit does not invalidate the potential for those in the future. For example, in the future, if we're able to characterize the data we're collecting on each interrupt, we may be able to inch toward information theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s = ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good accumulators for 2-monotone distributions, which would apply to timestamp counters, like random_get_entropy() or jiffies, but would not apply to our current combination of the two values, or to the various function addresses and register values we mix in. Alternatively, <https://eprint.iacr.org/2021/1002> shows that max-period linear functions with no non-trivial invariant subspace make good extractors, used in the form `s = f(s) ^ x`. However, this only works if the input data is both identical and independent, and obviously a collection of address values and counters fails; so it goes with theoretical papers. Future directions here may involve trying to characterize more precisely what we actually need to collect in the interrupt handler, and building something specific around that. However, as mentioned, the morass of data we're gathering at the interrupt handler presently defies characterization, and so we use SipHash for now, which works well and performs well. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 13:58:44 +00:00
memcpy(pool, fast_pool->pool, sizeof(pool));
fast_pool->count = 0;
random: defer fast pool mixing to worker On PREEMPT_RT, it's problematic to take spinlocks from hard irq handlers. We can fix this by deferring to a workqueue the dumping of the fast pool into the input pool. We accomplish this with some careful rules on fast_pool->count: - When it's incremented to >= 64, we schedule the work. - If the top bit is set, we never schedule the work, even if >= 64. - The worker is responsible for setting it back to 0 when it's done. There are two small issues around using workqueues for this purpose that we work around. The first issue is that mix_interrupt_randomness() might be migrated to another CPU during CPU hotplug. This issue is rectified by checking that it hasn't been migrated (after disabling irqs). If it has been migrated, then we set the count to zero, so that when the CPU comes online again, it can requeue the work. As part of this, we switch to using an atomic_t, so that the increment in the irq handler doesn't wipe out the zeroing if the CPU comes back online while this worker is running. The second issue is that, though relatively minor in effect, we probably want to make sure we get a consistent view of the pool onto the stack, in case it's interrupted by an irq while reading. To do this, we don't reenable irqs until after the copy. There are only 18 instructions between the cli and sti, so this is a pretty tiny window. Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Theodore Ts'o <tytso@mit.edu> Cc: Jonathan Neuschäfer <j.neuschaefer@gmx.net> Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Sultan Alsawaf <sultan@kerneltoast.com> Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-04 15:15:46 +00:00
fast_pool->last = jiffies;
local_irq_enable();
2022-02-13 17:25:07 +00:00
if (unlikely(crng_init == 0)) {
crng_pre_init_inject(pool, sizeof(pool), true);
mix_pool_bytes(pool, sizeof(pool));
} else {
mix_pool_bytes(pool, sizeof(pool));
credit_entropy_bits(1);
}
random: defer fast pool mixing to worker On PREEMPT_RT, it's problematic to take spinlocks from hard irq handlers. We can fix this by deferring to a workqueue the dumping of the fast pool into the input pool. We accomplish this with some careful rules on fast_pool->count: - When it's incremented to >= 64, we schedule the work. - If the top bit is set, we never schedule the work, even if >= 64. - The worker is responsible for setting it back to 0 when it's done. There are two small issues around using workqueues for this purpose that we work around. The first issue is that mix_interrupt_randomness() might be migrated to another CPU during CPU hotplug. This issue is rectified by checking that it hasn't been migrated (after disabling irqs). If it has been migrated, then we set the count to zero, so that when the CPU comes online again, it can requeue the work. As part of this, we switch to using an atomic_t, so that the increment in the irq handler doesn't wipe out the zeroing if the CPU comes back online while this worker is running. The second issue is that, though relatively minor in effect, we probably want to make sure we get a consistent view of the pool onto the stack, in case it's interrupted by an irq while reading. To do this, we don't reenable irqs until after the copy. There are only 18 instructions between the cli and sti, so this is a pretty tiny window. Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Theodore Ts'o <tytso@mit.edu> Cc: Jonathan Neuschäfer <j.neuschaefer@gmx.net> Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Sultan Alsawaf <sultan@kerneltoast.com> Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-04 15:15:46 +00:00
memzero_explicit(pool, sizeof(pool));
}
void add_interrupt_randomness(int irq)
{
random: defer fast pool mixing to worker On PREEMPT_RT, it's problematic to take spinlocks from hard irq handlers. We can fix this by deferring to a workqueue the dumping of the fast pool into the input pool. We accomplish this with some careful rules on fast_pool->count: - When it's incremented to >= 64, we schedule the work. - If the top bit is set, we never schedule the work, even if >= 64. - The worker is responsible for setting it back to 0 when it's done. There are two small issues around using workqueues for this purpose that we work around. The first issue is that mix_interrupt_randomness() might be migrated to another CPU during CPU hotplug. This issue is rectified by checking that it hasn't been migrated (after disabling irqs). If it has been migrated, then we set the count to zero, so that when the CPU comes online again, it can requeue the work. As part of this, we switch to using an atomic_t, so that the increment in the irq handler doesn't wipe out the zeroing if the CPU comes back online while this worker is running. The second issue is that, though relatively minor in effect, we probably want to make sure we get a consistent view of the pool onto the stack, in case it's interrupted by an irq while reading. To do this, we don't reenable irqs until after the copy. There are only 18 instructions between the cli and sti, so this is a pretty tiny window. Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Theodore Ts'o <tytso@mit.edu> Cc: Jonathan Neuschäfer <j.neuschaefer@gmx.net> Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Sultan Alsawaf <sultan@kerneltoast.com> Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-04 15:15:46 +00:00
enum { MIX_INFLIGHT = 1U << 31 };
cycles_t cycles = random_get_entropy();
unsigned long now = jiffies;
struct fast_pool *fast_pool = this_cpu_ptr(&irq_randomness);
struct pt_regs *regs = get_irq_regs();
random: defer fast pool mixing to worker On PREEMPT_RT, it's problematic to take spinlocks from hard irq handlers. We can fix this by deferring to a workqueue the dumping of the fast pool into the input pool. We accomplish this with some careful rules on fast_pool->count: - When it's incremented to >= 64, we schedule the work. - If the top bit is set, we never schedule the work, even if >= 64. - The worker is responsible for setting it back to 0 when it's done. There are two small issues around using workqueues for this purpose that we work around. The first issue is that mix_interrupt_randomness() might be migrated to another CPU during CPU hotplug. This issue is rectified by checking that it hasn't been migrated (after disabling irqs). If it has been migrated, then we set the count to zero, so that when the CPU comes online again, it can requeue the work. As part of this, we switch to using an atomic_t, so that the increment in the irq handler doesn't wipe out the zeroing if the CPU comes back online while this worker is running. The second issue is that, though relatively minor in effect, we probably want to make sure we get a consistent view of the pool onto the stack, in case it's interrupted by an irq while reading. To do this, we don't reenable irqs until after the copy. There are only 18 instructions between the cli and sti, so this is a pretty tiny window. Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Theodore Ts'o <tytso@mit.edu> Cc: Jonathan Neuschäfer <j.neuschaefer@gmx.net> Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Sultan Alsawaf <sultan@kerneltoast.com> Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-04 15:15:46 +00:00
unsigned int new_count;
random: use SipHash as interrupt entropy accumulator The current fast_mix() function is a piece of classic mailing list crypto, where it just sort of sprung up by an anonymous author without a lot of real analysis of what precisely it was accomplishing. As an ARX permutation alone, there are some easily searchable differential trails in it, and as a means of preventing malicious interrupts, it completely fails, since it xors new data into the entire state every time. It can't really be analyzed as a random permutation, because it clearly isn't, and it can't be analyzed as an interesting linear algebraic structure either, because it's also not that. There really is very little one can say about it in terms of entropy accumulation. It might diffuse bits, some of the time, maybe, we hope, I guess. But for the most part, it fails to accomplish anything concrete. As a reminder, the simple goal of add_interrupt_randomness() is to simply accumulate entropy until ~64 interrupts have elapsed, and then dump it into the main input pool, which uses a cryptographic hash. It would be nice to have something cryptographically strong in the interrupt handler itself, in case a malicious interrupt compromises a per-cpu fast pool within the 64 interrupts / 1 second window, and then inside of that same window somehow can control its return address and cycle counter, even if that's a bit far fetched. However, with a very CPU-limited budget, actually doing that remains an active research project (and perhaps there'll be something useful for Linux to come out of it). And while the abundance of caution would be nice, this isn't *currently* the security model, and we don't yet have a fast enough solution to make it our security model. Plus there's not exactly a pressing need to do that. (And for the avoidance of doubt, the actual cluster of 64 accumulated interrupts still gets dumped into our cryptographically secure input pool.) So, for now we are going to stick with the existing interrupt security model, which assumes that each cluster of 64 interrupt data samples is mostly non-malicious and not colluding with an infoleaker. With this as our goal, we have a few more choices, simply aiming to accumulate entropy, while discarding the least amount of it. We know from <https://eprint.iacr.org/2019/198> that random oracles, instantiated as computational hash functions, make good entropy accumulators and extractors, which is the justification for using BLAKE2s in the main input pool. As mentioned, we don't have that luxury here, but we also don't have the same security model requirements, because we're assuming that there aren't malicious inputs. A pseudorandom function instance can approximately behave like a random oracle, provided that the key is uniformly random. But since we're not concerned with malicious inputs, we can pick a fixed key, which is not secret, knowing that "nature" won't interact with a sufficiently chosen fixed key by accident. So we pick a PRF with a fixed initial key, and accumulate into it continuously, dumping the result every 64 interrupts into our cryptographically secure input pool. For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on 32-bit, which are already in use in the kernel's hsiphash family of functions and achieve the same performance as the function they replace. It would be nice to do two rounds, but we don't exactly have the CPU budget handy for that, and one round alone is already sufficient. As mentioned, we start with a fixed initial key (zeros is fine), and allow SipHash's symmetry breaking constants to turn that into a useful starting point. Also, since we're dumping the result (or half of it on 64-bit so as to tax our hash function the same amount on all platforms) into the cryptographically secure input pool, there's no point in finalizing SipHash's output, since it'll wind up being finalized by something much stronger. This means that all we need to do is use the ordinary round function word-by-word, as normal SipHash does. Simplified, the flow is as follows: Initialize: siphash_state_t state; siphash_init(&state, key={0, 0, 0, 0}); Update (accumulate) on interrupt: siphash_update(&state, interrupt_data_and_timing); Dump into input pool after 64 interrupts: blake2s_update(&input_pool, &state, sizeof(state) / 2); The result of all of this is that the security model is unchanged from before -- we assume non-malicious inputs -- yet we now implement that model with a stronger argument. I would like to emphasize, again, that the purpose of this commit is to improve the existing design, by making it analyzable, without changing any fundamental assumptions. There may well be value down the road in changing up the existing design, using something cryptographically strong, or simply using a ring buffer of samples rather than having a fast_mix() at all, or changing which and how much data we collect each interrupt so that we can use something linear, or a variety of other ideas. This commit does not invalidate the potential for those in the future. For example, in the future, if we're able to characterize the data we're collecting on each interrupt, we may be able to inch toward information theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s = ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good accumulators for 2-monotone distributions, which would apply to timestamp counters, like random_get_entropy() or jiffies, but would not apply to our current combination of the two values, or to the various function addresses and register values we mix in. Alternatively, <https://eprint.iacr.org/2021/1002> shows that max-period linear functions with no non-trivial invariant subspace make good extractors, used in the form `s = f(s) ^ x`. However, this only works if the input data is both identical and independent, and obviously a collection of address values and counters fails; so it goes with theoretical papers. Future directions here may involve trying to characterize more precisely what we actually need to collect in the interrupt handler, and building something specific around that. However, as mentioned, the morass of data we're gathering at the interrupt handler presently defies characterization, and so we use SipHash for now, which works well and performs well. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 13:58:44 +00:00
union {
u32 u32[4];
u64 u64[2];
unsigned long longs[16 / sizeof(long)];
} irq_data;
if (cycles == 0)
cycles = get_reg(fast_pool, regs);
if (sizeof(cycles) == 8)
random: use SipHash as interrupt entropy accumulator The current fast_mix() function is a piece of classic mailing list crypto, where it just sort of sprung up by an anonymous author without a lot of real analysis of what precisely it was accomplishing. As an ARX permutation alone, there are some easily searchable differential trails in it, and as a means of preventing malicious interrupts, it completely fails, since it xors new data into the entire state every time. It can't really be analyzed as a random permutation, because it clearly isn't, and it can't be analyzed as an interesting linear algebraic structure either, because it's also not that. There really is very little one can say about it in terms of entropy accumulation. It might diffuse bits, some of the time, maybe, we hope, I guess. But for the most part, it fails to accomplish anything concrete. As a reminder, the simple goal of add_interrupt_randomness() is to simply accumulate entropy until ~64 interrupts have elapsed, and then dump it into the main input pool, which uses a cryptographic hash. It would be nice to have something cryptographically strong in the interrupt handler itself, in case a malicious interrupt compromises a per-cpu fast pool within the 64 interrupts / 1 second window, and then inside of that same window somehow can control its return address and cycle counter, even if that's a bit far fetched. However, with a very CPU-limited budget, actually doing that remains an active research project (and perhaps there'll be something useful for Linux to come out of it). And while the abundance of caution would be nice, this isn't *currently* the security model, and we don't yet have a fast enough solution to make it our security model. Plus there's not exactly a pressing need to do that. (And for the avoidance of doubt, the actual cluster of 64 accumulated interrupts still gets dumped into our cryptographically secure input pool.) So, for now we are going to stick with the existing interrupt security model, which assumes that each cluster of 64 interrupt data samples is mostly non-malicious and not colluding with an infoleaker. With this as our goal, we have a few more choices, simply aiming to accumulate entropy, while discarding the least amount of it. We know from <https://eprint.iacr.org/2019/198> that random oracles, instantiated as computational hash functions, make good entropy accumulators and extractors, which is the justification for using BLAKE2s in the main input pool. As mentioned, we don't have that luxury here, but we also don't have the same security model requirements, because we're assuming that there aren't malicious inputs. A pseudorandom function instance can approximately behave like a random oracle, provided that the key is uniformly random. But since we're not concerned with malicious inputs, we can pick a fixed key, which is not secret, knowing that "nature" won't interact with a sufficiently chosen fixed key by accident. So we pick a PRF with a fixed initial key, and accumulate into it continuously, dumping the result every 64 interrupts into our cryptographically secure input pool. For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on 32-bit, which are already in use in the kernel's hsiphash family of functions and achieve the same performance as the function they replace. It would be nice to do two rounds, but we don't exactly have the CPU budget handy for that, and one round alone is already sufficient. As mentioned, we start with a fixed initial key (zeros is fine), and allow SipHash's symmetry breaking constants to turn that into a useful starting point. Also, since we're dumping the result (or half of it on 64-bit so as to tax our hash function the same amount on all platforms) into the cryptographically secure input pool, there's no point in finalizing SipHash's output, since it'll wind up being finalized by something much stronger. This means that all we need to do is use the ordinary round function word-by-word, as normal SipHash does. Simplified, the flow is as follows: Initialize: siphash_state_t state; siphash_init(&state, key={0, 0, 0, 0}); Update (accumulate) on interrupt: siphash_update(&state, interrupt_data_and_timing); Dump into input pool after 64 interrupts: blake2s_update(&input_pool, &state, sizeof(state) / 2); The result of all of this is that the security model is unchanged from before -- we assume non-malicious inputs -- yet we now implement that model with a stronger argument. I would like to emphasize, again, that the purpose of this commit is to improve the existing design, by making it analyzable, without changing any fundamental assumptions. There may well be value down the road in changing up the existing design, using something cryptographically strong, or simply using a ring buffer of samples rather than having a fast_mix() at all, or changing which and how much data we collect each interrupt so that we can use something linear, or a variety of other ideas. This commit does not invalidate the potential for those in the future. For example, in the future, if we're able to characterize the data we're collecting on each interrupt, we may be able to inch toward information theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s = ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good accumulators for 2-monotone distributions, which would apply to timestamp counters, like random_get_entropy() or jiffies, but would not apply to our current combination of the two values, or to the various function addresses and register values we mix in. Alternatively, <https://eprint.iacr.org/2021/1002> shows that max-period linear functions with no non-trivial invariant subspace make good extractors, used in the form `s = f(s) ^ x`. However, this only works if the input data is both identical and independent, and obviously a collection of address values and counters fails; so it goes with theoretical papers. Future directions here may involve trying to characterize more precisely what we actually need to collect in the interrupt handler, and building something specific around that. However, as mentioned, the morass of data we're gathering at the interrupt handler presently defies characterization, and so we use SipHash for now, which works well and performs well. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 13:58:44 +00:00
irq_data.u64[0] = cycles ^ rol64(now, 32) ^ irq;
else {
random: use SipHash as interrupt entropy accumulator The current fast_mix() function is a piece of classic mailing list crypto, where it just sort of sprung up by an anonymous author without a lot of real analysis of what precisely it was accomplishing. As an ARX permutation alone, there are some easily searchable differential trails in it, and as a means of preventing malicious interrupts, it completely fails, since it xors new data into the entire state every time. It can't really be analyzed as a random permutation, because it clearly isn't, and it can't be analyzed as an interesting linear algebraic structure either, because it's also not that. There really is very little one can say about it in terms of entropy accumulation. It might diffuse bits, some of the time, maybe, we hope, I guess. But for the most part, it fails to accomplish anything concrete. As a reminder, the simple goal of add_interrupt_randomness() is to simply accumulate entropy until ~64 interrupts have elapsed, and then dump it into the main input pool, which uses a cryptographic hash. It would be nice to have something cryptographically strong in the interrupt handler itself, in case a malicious interrupt compromises a per-cpu fast pool within the 64 interrupts / 1 second window, and then inside of that same window somehow can control its return address and cycle counter, even if that's a bit far fetched. However, with a very CPU-limited budget, actually doing that remains an active research project (and perhaps there'll be something useful for Linux to come out of it). And while the abundance of caution would be nice, this isn't *currently* the security model, and we don't yet have a fast enough solution to make it our security model. Plus there's not exactly a pressing need to do that. (And for the avoidance of doubt, the actual cluster of 64 accumulated interrupts still gets dumped into our cryptographically secure input pool.) So, for now we are going to stick with the existing interrupt security model, which assumes that each cluster of 64 interrupt data samples is mostly non-malicious and not colluding with an infoleaker. With this as our goal, we have a few more choices, simply aiming to accumulate entropy, while discarding the least amount of it. We know from <https://eprint.iacr.org/2019/198> that random oracles, instantiated as computational hash functions, make good entropy accumulators and extractors, which is the justification for using BLAKE2s in the main input pool. As mentioned, we don't have that luxury here, but we also don't have the same security model requirements, because we're assuming that there aren't malicious inputs. A pseudorandom function instance can approximately behave like a random oracle, provided that the key is uniformly random. But since we're not concerned with malicious inputs, we can pick a fixed key, which is not secret, knowing that "nature" won't interact with a sufficiently chosen fixed key by accident. So we pick a PRF with a fixed initial key, and accumulate into it continuously, dumping the result every 64 interrupts into our cryptographically secure input pool. For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on 32-bit, which are already in use in the kernel's hsiphash family of functions and achieve the same performance as the function they replace. It would be nice to do two rounds, but we don't exactly have the CPU budget handy for that, and one round alone is already sufficient. As mentioned, we start with a fixed initial key (zeros is fine), and allow SipHash's symmetry breaking constants to turn that into a useful starting point. Also, since we're dumping the result (or half of it on 64-bit so as to tax our hash function the same amount on all platforms) into the cryptographically secure input pool, there's no point in finalizing SipHash's output, since it'll wind up being finalized by something much stronger. This means that all we need to do is use the ordinary round function word-by-word, as normal SipHash does. Simplified, the flow is as follows: Initialize: siphash_state_t state; siphash_init(&state, key={0, 0, 0, 0}); Update (accumulate) on interrupt: siphash_update(&state, interrupt_data_and_timing); Dump into input pool after 64 interrupts: blake2s_update(&input_pool, &state, sizeof(state) / 2); The result of all of this is that the security model is unchanged from before -- we assume non-malicious inputs -- yet we now implement that model with a stronger argument. I would like to emphasize, again, that the purpose of this commit is to improve the existing design, by making it analyzable, without changing any fundamental assumptions. There may well be value down the road in changing up the existing design, using something cryptographically strong, or simply using a ring buffer of samples rather than having a fast_mix() at all, or changing which and how much data we collect each interrupt so that we can use something linear, or a variety of other ideas. This commit does not invalidate the potential for those in the future. For example, in the future, if we're able to characterize the data we're collecting on each interrupt, we may be able to inch toward information theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s = ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good accumulators for 2-monotone distributions, which would apply to timestamp counters, like random_get_entropy() or jiffies, but would not apply to our current combination of the two values, or to the various function addresses and register values we mix in. Alternatively, <https://eprint.iacr.org/2021/1002> shows that max-period linear functions with no non-trivial invariant subspace make good extractors, used in the form `s = f(s) ^ x`. However, this only works if the input data is both identical and independent, and obviously a collection of address values and counters fails; so it goes with theoretical papers. Future directions here may involve trying to characterize more precisely what we actually need to collect in the interrupt handler, and building something specific around that. However, as mentioned, the morass of data we're gathering at the interrupt handler presently defies characterization, and so we use SipHash for now, which works well and performs well. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 13:58:44 +00:00
irq_data.u32[0] = cycles ^ irq;
irq_data.u32[1] = now;
}
if (sizeof(unsigned long) == 8)
random: use SipHash as interrupt entropy accumulator The current fast_mix() function is a piece of classic mailing list crypto, where it just sort of sprung up by an anonymous author without a lot of real analysis of what precisely it was accomplishing. As an ARX permutation alone, there are some easily searchable differential trails in it, and as a means of preventing malicious interrupts, it completely fails, since it xors new data into the entire state every time. It can't really be analyzed as a random permutation, because it clearly isn't, and it can't be analyzed as an interesting linear algebraic structure either, because it's also not that. There really is very little one can say about it in terms of entropy accumulation. It might diffuse bits, some of the time, maybe, we hope, I guess. But for the most part, it fails to accomplish anything concrete. As a reminder, the simple goal of add_interrupt_randomness() is to simply accumulate entropy until ~64 interrupts have elapsed, and then dump it into the main input pool, which uses a cryptographic hash. It would be nice to have something cryptographically strong in the interrupt handler itself, in case a malicious interrupt compromises a per-cpu fast pool within the 64 interrupts / 1 second window, and then inside of that same window somehow can control its return address and cycle counter, even if that's a bit far fetched. However, with a very CPU-limited budget, actually doing that remains an active research project (and perhaps there'll be something useful for Linux to come out of it). And while the abundance of caution would be nice, this isn't *currently* the security model, and we don't yet have a fast enough solution to make it our security model. Plus there's not exactly a pressing need to do that. (And for the avoidance of doubt, the actual cluster of 64 accumulated interrupts still gets dumped into our cryptographically secure input pool.) So, for now we are going to stick with the existing interrupt security model, which assumes that each cluster of 64 interrupt data samples is mostly non-malicious and not colluding with an infoleaker. With this as our goal, we have a few more choices, simply aiming to accumulate entropy, while discarding the least amount of it. We know from <https://eprint.iacr.org/2019/198> that random oracles, instantiated as computational hash functions, make good entropy accumulators and extractors, which is the justification for using BLAKE2s in the main input pool. As mentioned, we don't have that luxury here, but we also don't have the same security model requirements, because we're assuming that there aren't malicious inputs. A pseudorandom function instance can approximately behave like a random oracle, provided that the key is uniformly random. But since we're not concerned with malicious inputs, we can pick a fixed key, which is not secret, knowing that "nature" won't interact with a sufficiently chosen fixed key by accident. So we pick a PRF with a fixed initial key, and accumulate into it continuously, dumping the result every 64 interrupts into our cryptographically secure input pool. For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on 32-bit, which are already in use in the kernel's hsiphash family of functions and achieve the same performance as the function they replace. It would be nice to do two rounds, but we don't exactly have the CPU budget handy for that, and one round alone is already sufficient. As mentioned, we start with a fixed initial key (zeros is fine), and allow SipHash's symmetry breaking constants to turn that into a useful starting point. Also, since we're dumping the result (or half of it on 64-bit so as to tax our hash function the same amount on all platforms) into the cryptographically secure input pool, there's no point in finalizing SipHash's output, since it'll wind up being finalized by something much stronger. This means that all we need to do is use the ordinary round function word-by-word, as normal SipHash does. Simplified, the flow is as follows: Initialize: siphash_state_t state; siphash_init(&state, key={0, 0, 0, 0}); Update (accumulate) on interrupt: siphash_update(&state, interrupt_data_and_timing); Dump into input pool after 64 interrupts: blake2s_update(&input_pool, &state, sizeof(state) / 2); The result of all of this is that the security model is unchanged from before -- we assume non-malicious inputs -- yet we now implement that model with a stronger argument. I would like to emphasize, again, that the purpose of this commit is to improve the existing design, by making it analyzable, without changing any fundamental assumptions. There may well be value down the road in changing up the existing design, using something cryptographically strong, or simply using a ring buffer of samples rather than having a fast_mix() at all, or changing which and how much data we collect each interrupt so that we can use something linear, or a variety of other ideas. This commit does not invalidate the potential for those in the future. For example, in the future, if we're able to characterize the data we're collecting on each interrupt, we may be able to inch toward information theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s = ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good accumulators for 2-monotone distributions, which would apply to timestamp counters, like random_get_entropy() or jiffies, but would not apply to our current combination of the two values, or to the various function addresses and register values we mix in. Alternatively, <https://eprint.iacr.org/2021/1002> shows that max-period linear functions with no non-trivial invariant subspace make good extractors, used in the form `s = f(s) ^ x`. However, this only works if the input data is both identical and independent, and obviously a collection of address values and counters fails; so it goes with theoretical papers. Future directions here may involve trying to characterize more precisely what we actually need to collect in the interrupt handler, and building something specific around that. However, as mentioned, the morass of data we're gathering at the interrupt handler presently defies characterization, and so we use SipHash for now, which works well and performs well. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 13:58:44 +00:00
irq_data.u64[1] = regs ? instruction_pointer(regs) : _RET_IP_;
else {
random: use SipHash as interrupt entropy accumulator The current fast_mix() function is a piece of classic mailing list crypto, where it just sort of sprung up by an anonymous author without a lot of real analysis of what precisely it was accomplishing. As an ARX permutation alone, there are some easily searchable differential trails in it, and as a means of preventing malicious interrupts, it completely fails, since it xors new data into the entire state every time. It can't really be analyzed as a random permutation, because it clearly isn't, and it can't be analyzed as an interesting linear algebraic structure either, because it's also not that. There really is very little one can say about it in terms of entropy accumulation. It might diffuse bits, some of the time, maybe, we hope, I guess. But for the most part, it fails to accomplish anything concrete. As a reminder, the simple goal of add_interrupt_randomness() is to simply accumulate entropy until ~64 interrupts have elapsed, and then dump it into the main input pool, which uses a cryptographic hash. It would be nice to have something cryptographically strong in the interrupt handler itself, in case a malicious interrupt compromises a per-cpu fast pool within the 64 interrupts / 1 second window, and then inside of that same window somehow can control its return address and cycle counter, even if that's a bit far fetched. However, with a very CPU-limited budget, actually doing that remains an active research project (and perhaps there'll be something useful for Linux to come out of it). And while the abundance of caution would be nice, this isn't *currently* the security model, and we don't yet have a fast enough solution to make it our security model. Plus there's not exactly a pressing need to do that. (And for the avoidance of doubt, the actual cluster of 64 accumulated interrupts still gets dumped into our cryptographically secure input pool.) So, for now we are going to stick with the existing interrupt security model, which assumes that each cluster of 64 interrupt data samples is mostly non-malicious and not colluding with an infoleaker. With this as our goal, we have a few more choices, simply aiming to accumulate entropy, while discarding the least amount of it. We know from <https://eprint.iacr.org/2019/198> that random oracles, instantiated as computational hash functions, make good entropy accumulators and extractors, which is the justification for using BLAKE2s in the main input pool. As mentioned, we don't have that luxury here, but we also don't have the same security model requirements, because we're assuming that there aren't malicious inputs. A pseudorandom function instance can approximately behave like a random oracle, provided that the key is uniformly random. But since we're not concerned with malicious inputs, we can pick a fixed key, which is not secret, knowing that "nature" won't interact with a sufficiently chosen fixed key by accident. So we pick a PRF with a fixed initial key, and accumulate into it continuously, dumping the result every 64 interrupts into our cryptographically secure input pool. For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on 32-bit, which are already in use in the kernel's hsiphash family of functions and achieve the same performance as the function they replace. It would be nice to do two rounds, but we don't exactly have the CPU budget handy for that, and one round alone is already sufficient. As mentioned, we start with a fixed initial key (zeros is fine), and allow SipHash's symmetry breaking constants to turn that into a useful starting point. Also, since we're dumping the result (or half of it on 64-bit so as to tax our hash function the same amount on all platforms) into the cryptographically secure input pool, there's no point in finalizing SipHash's output, since it'll wind up being finalized by something much stronger. This means that all we need to do is use the ordinary round function word-by-word, as normal SipHash does. Simplified, the flow is as follows: Initialize: siphash_state_t state; siphash_init(&state, key={0, 0, 0, 0}); Update (accumulate) on interrupt: siphash_update(&state, interrupt_data_and_timing); Dump into input pool after 64 interrupts: blake2s_update(&input_pool, &state, sizeof(state) / 2); The result of all of this is that the security model is unchanged from before -- we assume non-malicious inputs -- yet we now implement that model with a stronger argument. I would like to emphasize, again, that the purpose of this commit is to improve the existing design, by making it analyzable, without changing any fundamental assumptions. There may well be value down the road in changing up the existing design, using something cryptographically strong, or simply using a ring buffer of samples rather than having a fast_mix() at all, or changing which and how much data we collect each interrupt so that we can use something linear, or a variety of other ideas. This commit does not invalidate the potential for those in the future. For example, in the future, if we're able to characterize the data we're collecting on each interrupt, we may be able to inch toward information theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s = ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good accumulators for 2-monotone distributions, which would apply to timestamp counters, like random_get_entropy() or jiffies, but would not apply to our current combination of the two values, or to the various function addresses and register values we mix in. Alternatively, <https://eprint.iacr.org/2021/1002> shows that max-period linear functions with no non-trivial invariant subspace make good extractors, used in the form `s = f(s) ^ x`. However, this only works if the input data is both identical and independent, and obviously a collection of address values and counters fails; so it goes with theoretical papers. Future directions here may involve trying to characterize more precisely what we actually need to collect in the interrupt handler, and building something specific around that. However, as mentioned, the morass of data we're gathering at the interrupt handler presently defies characterization, and so we use SipHash for now, which works well and performs well. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 13:58:44 +00:00
irq_data.u32[2] = regs ? instruction_pointer(regs) : _RET_IP_;
irq_data.u32[3] = get_reg(fast_pool, regs);
}
random: use SipHash as interrupt entropy accumulator The current fast_mix() function is a piece of classic mailing list crypto, where it just sort of sprung up by an anonymous author without a lot of real analysis of what precisely it was accomplishing. As an ARX permutation alone, there are some easily searchable differential trails in it, and as a means of preventing malicious interrupts, it completely fails, since it xors new data into the entire state every time. It can't really be analyzed as a random permutation, because it clearly isn't, and it can't be analyzed as an interesting linear algebraic structure either, because it's also not that. There really is very little one can say about it in terms of entropy accumulation. It might diffuse bits, some of the time, maybe, we hope, I guess. But for the most part, it fails to accomplish anything concrete. As a reminder, the simple goal of add_interrupt_randomness() is to simply accumulate entropy until ~64 interrupts have elapsed, and then dump it into the main input pool, which uses a cryptographic hash. It would be nice to have something cryptographically strong in the interrupt handler itself, in case a malicious interrupt compromises a per-cpu fast pool within the 64 interrupts / 1 second window, and then inside of that same window somehow can control its return address and cycle counter, even if that's a bit far fetched. However, with a very CPU-limited budget, actually doing that remains an active research project (and perhaps there'll be something useful for Linux to come out of it). And while the abundance of caution would be nice, this isn't *currently* the security model, and we don't yet have a fast enough solution to make it our security model. Plus there's not exactly a pressing need to do that. (And for the avoidance of doubt, the actual cluster of 64 accumulated interrupts still gets dumped into our cryptographically secure input pool.) So, for now we are going to stick with the existing interrupt security model, which assumes that each cluster of 64 interrupt data samples is mostly non-malicious and not colluding with an infoleaker. With this as our goal, we have a few more choices, simply aiming to accumulate entropy, while discarding the least amount of it. We know from <https://eprint.iacr.org/2019/198> that random oracles, instantiated as computational hash functions, make good entropy accumulators and extractors, which is the justification for using BLAKE2s in the main input pool. As mentioned, we don't have that luxury here, but we also don't have the same security model requirements, because we're assuming that there aren't malicious inputs. A pseudorandom function instance can approximately behave like a random oracle, provided that the key is uniformly random. But since we're not concerned with malicious inputs, we can pick a fixed key, which is not secret, knowing that "nature" won't interact with a sufficiently chosen fixed key by accident. So we pick a PRF with a fixed initial key, and accumulate into it continuously, dumping the result every 64 interrupts into our cryptographically secure input pool. For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on 32-bit, which are already in use in the kernel's hsiphash family of functions and achieve the same performance as the function they replace. It would be nice to do two rounds, but we don't exactly have the CPU budget handy for that, and one round alone is already sufficient. As mentioned, we start with a fixed initial key (zeros is fine), and allow SipHash's symmetry breaking constants to turn that into a useful starting point. Also, since we're dumping the result (or half of it on 64-bit so as to tax our hash function the same amount on all platforms) into the cryptographically secure input pool, there's no point in finalizing SipHash's output, since it'll wind up being finalized by something much stronger. This means that all we need to do is use the ordinary round function word-by-word, as normal SipHash does. Simplified, the flow is as follows: Initialize: siphash_state_t state; siphash_init(&state, key={0, 0, 0, 0}); Update (accumulate) on interrupt: siphash_update(&state, interrupt_data_and_timing); Dump into input pool after 64 interrupts: blake2s_update(&input_pool, &state, sizeof(state) / 2); The result of all of this is that the security model is unchanged from before -- we assume non-malicious inputs -- yet we now implement that model with a stronger argument. I would like to emphasize, again, that the purpose of this commit is to improve the existing design, by making it analyzable, without changing any fundamental assumptions. There may well be value down the road in changing up the existing design, using something cryptographically strong, or simply using a ring buffer of samples rather than having a fast_mix() at all, or changing which and how much data we collect each interrupt so that we can use something linear, or a variety of other ideas. This commit does not invalidate the potential for those in the future. For example, in the future, if we're able to characterize the data we're collecting on each interrupt, we may be able to inch toward information theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s = ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good accumulators for 2-monotone distributions, which would apply to timestamp counters, like random_get_entropy() or jiffies, but would not apply to our current combination of the two values, or to the various function addresses and register values we mix in. Alternatively, <https://eprint.iacr.org/2021/1002> shows that max-period linear functions with no non-trivial invariant subspace make good extractors, used in the form `s = f(s) ^ x`. However, this only works if the input data is both identical and independent, and obviously a collection of address values and counters fails; so it goes with theoretical papers. Future directions here may involve trying to characterize more precisely what we actually need to collect in the interrupt handler, and building something specific around that. However, as mentioned, the morass of data we're gathering at the interrupt handler presently defies characterization, and so we use SipHash for now, which works well and performs well. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 13:58:44 +00:00
fast_mix(fast_pool->pool, irq_data.longs);
new_count = ++fast_pool->count;
random: defer fast pool mixing to worker On PREEMPT_RT, it's problematic to take spinlocks from hard irq handlers. We can fix this by deferring to a workqueue the dumping of the fast pool into the input pool. We accomplish this with some careful rules on fast_pool->count: - When it's incremented to >= 64, we schedule the work. - If the top bit is set, we never schedule the work, even if >= 64. - The worker is responsible for setting it back to 0 when it's done. There are two small issues around using workqueues for this purpose that we work around. The first issue is that mix_interrupt_randomness() might be migrated to another CPU during CPU hotplug. This issue is rectified by checking that it hasn't been migrated (after disabling irqs). If it has been migrated, then we set the count to zero, so that when the CPU comes online again, it can requeue the work. As part of this, we switch to using an atomic_t, so that the increment in the irq handler doesn't wipe out the zeroing if the CPU comes back online while this worker is running. The second issue is that, though relatively minor in effect, we probably want to make sure we get a consistent view of the pool onto the stack, in case it's interrupted by an irq while reading. To do this, we don't reenable irqs until after the copy. There are only 18 instructions between the cli and sti, so this is a pretty tiny window. Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Theodore Ts'o <tytso@mit.edu> Cc: Jonathan Neuschäfer <j.neuschaefer@gmx.net> Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Sultan Alsawaf <sultan@kerneltoast.com> Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-04 15:15:46 +00:00
if (new_count & MIX_INFLIGHT)
return;
2022-02-13 17:25:07 +00:00
if (new_count < 64 && (!time_after(now, fast_pool->last + HZ) ||
unlikely(crng_init == 0)))
return;
random: defer fast pool mixing to worker On PREEMPT_RT, it's problematic to take spinlocks from hard irq handlers. We can fix this by deferring to a workqueue the dumping of the fast pool into the input pool. We accomplish this with some careful rules on fast_pool->count: - When it's incremented to >= 64, we schedule the work. - If the top bit is set, we never schedule the work, even if >= 64. - The worker is responsible for setting it back to 0 when it's done. There are two small issues around using workqueues for this purpose that we work around. The first issue is that mix_interrupt_randomness() might be migrated to another CPU during CPU hotplug. This issue is rectified by checking that it hasn't been migrated (after disabling irqs). If it has been migrated, then we set the count to zero, so that when the CPU comes online again, it can requeue the work. As part of this, we switch to using an atomic_t, so that the increment in the irq handler doesn't wipe out the zeroing if the CPU comes back online while this worker is running. The second issue is that, though relatively minor in effect, we probably want to make sure we get a consistent view of the pool onto the stack, in case it's interrupted by an irq while reading. To do this, we don't reenable irqs until after the copy. There are only 18 instructions between the cli and sti, so this is a pretty tiny window. Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Theodore Ts'o <tytso@mit.edu> Cc: Jonathan Neuschäfer <j.neuschaefer@gmx.net> Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Sultan Alsawaf <sultan@kerneltoast.com> Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-04 15:15:46 +00:00
if (unlikely(!fast_pool->mix.func))
INIT_WORK(&fast_pool->mix, mix_interrupt_randomness);
fast_pool->count |= MIX_INFLIGHT;
random: defer fast pool mixing to worker On PREEMPT_RT, it's problematic to take spinlocks from hard irq handlers. We can fix this by deferring to a workqueue the dumping of the fast pool into the input pool. We accomplish this with some careful rules on fast_pool->count: - When it's incremented to >= 64, we schedule the work. - If the top bit is set, we never schedule the work, even if >= 64. - The worker is responsible for setting it back to 0 when it's done. There are two small issues around using workqueues for this purpose that we work around. The first issue is that mix_interrupt_randomness() might be migrated to another CPU during CPU hotplug. This issue is rectified by checking that it hasn't been migrated (after disabling irqs). If it has been migrated, then we set the count to zero, so that when the CPU comes online again, it can requeue the work. As part of this, we switch to using an atomic_t, so that the increment in the irq handler doesn't wipe out the zeroing if the CPU comes back online while this worker is running. The second issue is that, though relatively minor in effect, we probably want to make sure we get a consistent view of the pool onto the stack, in case it's interrupted by an irq while reading. To do this, we don't reenable irqs until after the copy. There are only 18 instructions between the cli and sti, so this is a pretty tiny window. Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Theodore Ts'o <tytso@mit.edu> Cc: Jonathan Neuschäfer <j.neuschaefer@gmx.net> Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de> Reviewed-by: Sultan Alsawaf <sultan@kerneltoast.com> Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-04 15:15:46 +00:00
queue_work_on(raw_smp_processor_id(), system_highpri_wq, &fast_pool->mix);
}
EXPORT_SYMBOL_GPL(add_interrupt_randomness);
random: try to actively add entropy rather than passively wait for it For 5.3 we had to revert a nice ext4 IO pattern improvement, because it caused a bootup regression due to lack of entropy at bootup together with arguably broken user space that was asking for secure random numbers when it really didn't need to. See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug"). This aims to solve the issue by actively generating entropy noise using the CPU cycle counter when waiting for the random number generator to initialize. This only works when you have a high-frequency time stamp counter available, but that's the case on all modern x86 CPU's, and on most other modern CPU's too. What we do is to generate jitter entropy from the CPU cycle counter under a somewhat complex load: calling the scheduler while also guaranteeing a certain amount of timing noise by also triggering a timer. I'm sure we can tweak this, and that people will want to look at other alternatives, but there's been a number of papers written on jitter entropy, and this should really be fairly conservative by crediting one bit of entropy for every timer-induced jump in the cycle counter. Not because the timer itself would be all that unpredictable, but because the interaction between the timer and the loop is going to be. Even if (and perhaps particularly if) the timer actually happens on another CPU, the cacheline interaction between the loop that reads the cycle counter and the timer itself firing is going to add perturbations to the cycle counter values that get mixed into the entropy pool. As Thomas pointed out, with a modern out-of-order CPU, even quite simple loops show a fair amount of hard-to-predict timing variability even in the absense of external interrupts. But this tries to take that further by actually having a fairly complex interaction. This is not going to solve the entropy issue for architectures that have no CPU cycle counter, but it's not clear how (and if) that is solvable, and the hardware in question is largely starting to be irrelevant. And by doing this we can at least avoid some of the even more contentious approaches (like making the entropy waiting time out in order to avoid the possibly unbounded waiting). Cc: Ahmed Darwish <darwish.07@gmail.com> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Theodore Ts'o <tytso@mit.edu> Cc: Nicholas Mc Guire <hofrat@opentech.at> Cc: Andy Lutomirski <luto@kernel.org> Cc: Kees Cook <keescook@chromium.org> Cc: Willy Tarreau <w@1wt.eu> Cc: Alexander E. Patrakov <patrakov@gmail.com> Cc: Lennart Poettering <mzxreary@0pointer.de> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 23:53:52 +00:00
/*
* Each time the timer fires, we expect that we got an unpredictable
* jump in the cycle counter. Even if the timer is running on another
* CPU, the timer activity will be touching the stack of the CPU that is
* generating entropy..
*
* Note that we don't re-arm the timer in the timer itself - we are
* happy to be scheduled away, since that just makes the load more
* complex, but we do not want the timer to keep ticking unless the
* entropy loop is running.
*
* So the re-arming always happens in the entropy loop itself.
*/
static void entropy_timer(struct timer_list *t)
{
credit_entropy_bits(1);
random: try to actively add entropy rather than passively wait for it For 5.3 we had to revert a nice ext4 IO pattern improvement, because it caused a bootup regression due to lack of entropy at bootup together with arguably broken user space that was asking for secure random numbers when it really didn't need to. See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug"). This aims to solve the issue by actively generating entropy noise using the CPU cycle counter when waiting for the random number generator to initialize. This only works when you have a high-frequency time stamp counter available, but that's the case on all modern x86 CPU's, and on most other modern CPU's too. What we do is to generate jitter entropy from the CPU cycle counter under a somewhat complex load: calling the scheduler while also guaranteeing a certain amount of timing noise by also triggering a timer. I'm sure we can tweak this, and that people will want to look at other alternatives, but there's been a number of papers written on jitter entropy, and this should really be fairly conservative by crediting one bit of entropy for every timer-induced jump in the cycle counter. Not because the timer itself would be all that unpredictable, but because the interaction between the timer and the loop is going to be. Even if (and perhaps particularly if) the timer actually happens on another CPU, the cacheline interaction between the loop that reads the cycle counter and the timer itself firing is going to add perturbations to the cycle counter values that get mixed into the entropy pool. As Thomas pointed out, with a modern out-of-order CPU, even quite simple loops show a fair amount of hard-to-predict timing variability even in the absense of external interrupts. But this tries to take that further by actually having a fairly complex interaction. This is not going to solve the entropy issue for architectures that have no CPU cycle counter, but it's not clear how (and if) that is solvable, and the hardware in question is largely starting to be irrelevant. And by doing this we can at least avoid some of the even more contentious approaches (like making the entropy waiting time out in order to avoid the possibly unbounded waiting). Cc: Ahmed Darwish <darwish.07@gmail.com> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Theodore Ts'o <tytso@mit.edu> Cc: Nicholas Mc Guire <hofrat@opentech.at> Cc: Andy Lutomirski <luto@kernel.org> Cc: Kees Cook <keescook@chromium.org> Cc: Willy Tarreau <w@1wt.eu> Cc: Alexander E. Patrakov <patrakov@gmail.com> Cc: Lennart Poettering <mzxreary@0pointer.de> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 23:53:52 +00:00
}
/*
* If we have an actual cycle counter, see if we can
* generate enough entropy with timing noise
*/
static void try_to_generate_entropy(void)
{
struct {
cycles_t cycles;
random: try to actively add entropy rather than passively wait for it For 5.3 we had to revert a nice ext4 IO pattern improvement, because it caused a bootup regression due to lack of entropy at bootup together with arguably broken user space that was asking for secure random numbers when it really didn't need to. See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug"). This aims to solve the issue by actively generating entropy noise using the CPU cycle counter when waiting for the random number generator to initialize. This only works when you have a high-frequency time stamp counter available, but that's the case on all modern x86 CPU's, and on most other modern CPU's too. What we do is to generate jitter entropy from the CPU cycle counter under a somewhat complex load: calling the scheduler while also guaranteeing a certain amount of timing noise by also triggering a timer. I'm sure we can tweak this, and that people will want to look at other alternatives, but there's been a number of papers written on jitter entropy, and this should really be fairly conservative by crediting one bit of entropy for every timer-induced jump in the cycle counter. Not because the timer itself would be all that unpredictable, but because the interaction between the timer and the loop is going to be. Even if (and perhaps particularly if) the timer actually happens on another CPU, the cacheline interaction between the loop that reads the cycle counter and the timer itself firing is going to add perturbations to the cycle counter values that get mixed into the entropy pool. As Thomas pointed out, with a modern out-of-order CPU, even quite simple loops show a fair amount of hard-to-predict timing variability even in the absense of external interrupts. But this tries to take that further by actually having a fairly complex interaction. This is not going to solve the entropy issue for architectures that have no CPU cycle counter, but it's not clear how (and if) that is solvable, and the hardware in question is largely starting to be irrelevant. And by doing this we can at least avoid some of the even more contentious approaches (like making the entropy waiting time out in order to avoid the possibly unbounded waiting). Cc: Ahmed Darwish <darwish.07@gmail.com> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Theodore Ts'o <tytso@mit.edu> Cc: Nicholas Mc Guire <hofrat@opentech.at> Cc: Andy Lutomirski <luto@kernel.org> Cc: Kees Cook <keescook@chromium.org> Cc: Willy Tarreau <w@1wt.eu> Cc: Alexander E. Patrakov <patrakov@gmail.com> Cc: Lennart Poettering <mzxreary@0pointer.de> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 23:53:52 +00:00
struct timer_list timer;
} stack;
stack.cycles = random_get_entropy();
random: try to actively add entropy rather than passively wait for it For 5.3 we had to revert a nice ext4 IO pattern improvement, because it caused a bootup regression due to lack of entropy at bootup together with arguably broken user space that was asking for secure random numbers when it really didn't need to. See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug"). This aims to solve the issue by actively generating entropy noise using the CPU cycle counter when waiting for the random number generator to initialize. This only works when you have a high-frequency time stamp counter available, but that's the case on all modern x86 CPU's, and on most other modern CPU's too. What we do is to generate jitter entropy from the CPU cycle counter under a somewhat complex load: calling the scheduler while also guaranteeing a certain amount of timing noise by also triggering a timer. I'm sure we can tweak this, and that people will want to look at other alternatives, but there's been a number of papers written on jitter entropy, and this should really be fairly conservative by crediting one bit of entropy for every timer-induced jump in the cycle counter. Not because the timer itself would be all that unpredictable, but because the interaction between the timer and the loop is going to be. Even if (and perhaps particularly if) the timer actually happens on another CPU, the cacheline interaction between the loop that reads the cycle counter and the timer itself firing is going to add perturbations to the cycle counter values that get mixed into the entropy pool. As Thomas pointed out, with a modern out-of-order CPU, even quite simple loops show a fair amount of hard-to-predict timing variability even in the absense of external interrupts. But this tries to take that further by actually having a fairly complex interaction. This is not going to solve the entropy issue for architectures that have no CPU cycle counter, but it's not clear how (and if) that is solvable, and the hardware in question is largely starting to be irrelevant. And by doing this we can at least avoid some of the even more contentious approaches (like making the entropy waiting time out in order to avoid the possibly unbounded waiting). Cc: Ahmed Darwish <darwish.07@gmail.com> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Theodore Ts'o <tytso@mit.edu> Cc: Nicholas Mc Guire <hofrat@opentech.at> Cc: Andy Lutomirski <luto@kernel.org> Cc: Kees Cook <keescook@chromium.org> Cc: Willy Tarreau <w@1wt.eu> Cc: Alexander E. Patrakov <patrakov@gmail.com> Cc: Lennart Poettering <mzxreary@0pointer.de> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 23:53:52 +00:00
/* Slow counter - or none. Don't even bother */
if (stack.cycles == random_get_entropy())
random: try to actively add entropy rather than passively wait for it For 5.3 we had to revert a nice ext4 IO pattern improvement, because it caused a bootup regression due to lack of entropy at bootup together with arguably broken user space that was asking for secure random numbers when it really didn't need to. See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug"). This aims to solve the issue by actively generating entropy noise using the CPU cycle counter when waiting for the random number generator to initialize. This only works when you have a high-frequency time stamp counter available, but that's the case on all modern x86 CPU's, and on most other modern CPU's too. What we do is to generate jitter entropy from the CPU cycle counter under a somewhat complex load: calling the scheduler while also guaranteeing a certain amount of timing noise by also triggering a timer. I'm sure we can tweak this, and that people will want to look at other alternatives, but there's been a number of papers written on jitter entropy, and this should really be fairly conservative by crediting one bit of entropy for every timer-induced jump in the cycle counter. Not because the timer itself would be all that unpredictable, but because the interaction between the timer and the loop is going to be. Even if (and perhaps particularly if) the timer actually happens on another CPU, the cacheline interaction between the loop that reads the cycle counter and the timer itself firing is going to add perturbations to the cycle counter values that get mixed into the entropy pool. As Thomas pointed out, with a modern out-of-order CPU, even quite simple loops show a fair amount of hard-to-predict timing variability even in the absense of external interrupts. But this tries to take that further by actually having a fairly complex interaction. This is not going to solve the entropy issue for architectures that have no CPU cycle counter, but it's not clear how (and if) that is solvable, and the hardware in question is largely starting to be irrelevant. And by doing this we can at least avoid some of the even more contentious approaches (like making the entropy waiting time out in order to avoid the possibly unbounded waiting). Cc: Ahmed Darwish <darwish.07@gmail.com> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Theodore Ts'o <tytso@mit.edu> Cc: Nicholas Mc Guire <hofrat@opentech.at> Cc: Andy Lutomirski <luto@kernel.org> Cc: Kees Cook <keescook@chromium.org> Cc: Willy Tarreau <w@1wt.eu> Cc: Alexander E. Patrakov <patrakov@gmail.com> Cc: Lennart Poettering <mzxreary@0pointer.de> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 23:53:52 +00:00
return;
timer_setup_on_stack(&stack.timer, entropy_timer, 0);
while (!crng_ready() && !signal_pending(current)) {
random: try to actively add entropy rather than passively wait for it For 5.3 we had to revert a nice ext4 IO pattern improvement, because it caused a bootup regression due to lack of entropy at bootup together with arguably broken user space that was asking for secure random numbers when it really didn't need to. See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug"). This aims to solve the issue by actively generating entropy noise using the CPU cycle counter when waiting for the random number generator to initialize. This only works when you have a high-frequency time stamp counter available, but that's the case on all modern x86 CPU's, and on most other modern CPU's too. What we do is to generate jitter entropy from the CPU cycle counter under a somewhat complex load: calling the scheduler while also guaranteeing a certain amount of timing noise by also triggering a timer. I'm sure we can tweak this, and that people will want to look at other alternatives, but there's been a number of papers written on jitter entropy, and this should really be fairly conservative by crediting one bit of entropy for every timer-induced jump in the cycle counter. Not because the timer itself would be all that unpredictable, but because the interaction between the timer and the loop is going to be. Even if (and perhaps particularly if) the timer actually happens on another CPU, the cacheline interaction between the loop that reads the cycle counter and the timer itself firing is going to add perturbations to the cycle counter values that get mixed into the entropy pool. As Thomas pointed out, with a modern out-of-order CPU, even quite simple loops show a fair amount of hard-to-predict timing variability even in the absense of external interrupts. But this tries to take that further by actually having a fairly complex interaction. This is not going to solve the entropy issue for architectures that have no CPU cycle counter, but it's not clear how (and if) that is solvable, and the hardware in question is largely starting to be irrelevant. And by doing this we can at least avoid some of the even more contentious approaches (like making the entropy waiting time out in order to avoid the possibly unbounded waiting). Cc: Ahmed Darwish <darwish.07@gmail.com> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Theodore Ts'o <tytso@mit.edu> Cc: Nicholas Mc Guire <hofrat@opentech.at> Cc: Andy Lutomirski <luto@kernel.org> Cc: Kees Cook <keescook@chromium.org> Cc: Willy Tarreau <w@1wt.eu> Cc: Alexander E. Patrakov <patrakov@gmail.com> Cc: Lennart Poettering <mzxreary@0pointer.de> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 23:53:52 +00:00
if (!timer_pending(&stack.timer))
mod_timer(&stack.timer, jiffies + 1);
mix_pool_bytes(&stack.cycles, sizeof(stack.cycles));
random: try to actively add entropy rather than passively wait for it For 5.3 we had to revert a nice ext4 IO pattern improvement, because it caused a bootup regression due to lack of entropy at bootup together with arguably broken user space that was asking for secure random numbers when it really didn't need to. See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug"). This aims to solve the issue by actively generating entropy noise using the CPU cycle counter when waiting for the random number generator to initialize. This only works when you have a high-frequency time stamp counter available, but that's the case on all modern x86 CPU's, and on most other modern CPU's too. What we do is to generate jitter entropy from the CPU cycle counter under a somewhat complex load: calling the scheduler while also guaranteeing a certain amount of timing noise by also triggering a timer. I'm sure we can tweak this, and that people will want to look at other alternatives, but there's been a number of papers written on jitter entropy, and this should really be fairly conservative by crediting one bit of entropy for every timer-induced jump in the cycle counter. Not because the timer itself would be all that unpredictable, but because the interaction between the timer and the loop is going to be. Even if (and perhaps particularly if) the timer actually happens on another CPU, the cacheline interaction between the loop that reads the cycle counter and the timer itself firing is going to add perturbations to the cycle counter values that get mixed into the entropy pool. As Thomas pointed out, with a modern out-of-order CPU, even quite simple loops show a fair amount of hard-to-predict timing variability even in the absense of external interrupts. But this tries to take that further by actually having a fairly complex interaction. This is not going to solve the entropy issue for architectures that have no CPU cycle counter, but it's not clear how (and if) that is solvable, and the hardware in question is largely starting to be irrelevant. And by doing this we can at least avoid some of the even more contentious approaches (like making the entropy waiting time out in order to avoid the possibly unbounded waiting). Cc: Ahmed Darwish <darwish.07@gmail.com> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Theodore Ts'o <tytso@mit.edu> Cc: Nicholas Mc Guire <hofrat@opentech.at> Cc: Andy Lutomirski <luto@kernel.org> Cc: Kees Cook <keescook@chromium.org> Cc: Willy Tarreau <w@1wt.eu> Cc: Alexander E. Patrakov <patrakov@gmail.com> Cc: Lennart Poettering <mzxreary@0pointer.de> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 23:53:52 +00:00
schedule();
stack.cycles = random_get_entropy();
random: try to actively add entropy rather than passively wait for it For 5.3 we had to revert a nice ext4 IO pattern improvement, because it caused a bootup regression due to lack of entropy at bootup together with arguably broken user space that was asking for secure random numbers when it really didn't need to. See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug"). This aims to solve the issue by actively generating entropy noise using the CPU cycle counter when waiting for the random number generator to initialize. This only works when you have a high-frequency time stamp counter available, but that's the case on all modern x86 CPU's, and on most other modern CPU's too. What we do is to generate jitter entropy from the CPU cycle counter under a somewhat complex load: calling the scheduler while also guaranteeing a certain amount of timing noise by also triggering a timer. I'm sure we can tweak this, and that people will want to look at other alternatives, but there's been a number of papers written on jitter entropy, and this should really be fairly conservative by crediting one bit of entropy for every timer-induced jump in the cycle counter. Not because the timer itself would be all that unpredictable, but because the interaction between the timer and the loop is going to be. Even if (and perhaps particularly if) the timer actually happens on another CPU, the cacheline interaction between the loop that reads the cycle counter and the timer itself firing is going to add perturbations to the cycle counter values that get mixed into the entropy pool. As Thomas pointed out, with a modern out-of-order CPU, even quite simple loops show a fair amount of hard-to-predict timing variability even in the absense of external interrupts. But this tries to take that further by actually having a fairly complex interaction. This is not going to solve the entropy issue for architectures that have no CPU cycle counter, but it's not clear how (and if) that is solvable, and the hardware in question is largely starting to be irrelevant. And by doing this we can at least avoid some of the even more contentious approaches (like making the entropy waiting time out in order to avoid the possibly unbounded waiting). Cc: Ahmed Darwish <darwish.07@gmail.com> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Theodore Ts'o <tytso@mit.edu> Cc: Nicholas Mc Guire <hofrat@opentech.at> Cc: Andy Lutomirski <luto@kernel.org> Cc: Kees Cook <keescook@chromium.org> Cc: Willy Tarreau <w@1wt.eu> Cc: Alexander E. Patrakov <patrakov@gmail.com> Cc: Lennart Poettering <mzxreary@0pointer.de> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 23:53:52 +00:00
}
del_timer_sync(&stack.timer);
destroy_timer_on_stack(&stack.timer);
mix_pool_bytes(&stack.cycles, sizeof(stack.cycles));
random: try to actively add entropy rather than passively wait for it For 5.3 we had to revert a nice ext4 IO pattern improvement, because it caused a bootup regression due to lack of entropy at bootup together with arguably broken user space that was asking for secure random numbers when it really didn't need to. See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug"). This aims to solve the issue by actively generating entropy noise using the CPU cycle counter when waiting for the random number generator to initialize. This only works when you have a high-frequency time stamp counter available, but that's the case on all modern x86 CPU's, and on most other modern CPU's too. What we do is to generate jitter entropy from the CPU cycle counter under a somewhat complex load: calling the scheduler while also guaranteeing a certain amount of timing noise by also triggering a timer. I'm sure we can tweak this, and that people will want to look at other alternatives, but there's been a number of papers written on jitter entropy, and this should really be fairly conservative by crediting one bit of entropy for every timer-induced jump in the cycle counter. Not because the timer itself would be all that unpredictable, but because the interaction between the timer and the loop is going to be. Even if (and perhaps particularly if) the timer actually happens on another CPU, the cacheline interaction between the loop that reads the cycle counter and the timer itself firing is going to add perturbations to the cycle counter values that get mixed into the entropy pool. As Thomas pointed out, with a modern out-of-order CPU, even quite simple loops show a fair amount of hard-to-predict timing variability even in the absense of external interrupts. But this tries to take that further by actually having a fairly complex interaction. This is not going to solve the entropy issue for architectures that have no CPU cycle counter, but it's not clear how (and if) that is solvable, and the hardware in question is largely starting to be irrelevant. And by doing this we can at least avoid some of the even more contentious approaches (like making the entropy waiting time out in order to avoid the possibly unbounded waiting). Cc: Ahmed Darwish <darwish.07@gmail.com> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Theodore Ts'o <tytso@mit.edu> Cc: Nicholas Mc Guire <hofrat@opentech.at> Cc: Andy Lutomirski <luto@kernel.org> Cc: Kees Cook <keescook@chromium.org> Cc: Willy Tarreau <w@1wt.eu> Cc: Alexander E. Patrakov <patrakov@gmail.com> Cc: Lennart Poettering <mzxreary@0pointer.de> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 23:53:52 +00:00
}
/**********************************************************************
*
* Userspace reader/writer interfaces.
*
* getrandom(2) is the primary modern interface into the RNG and should
* be used in preference to anything else.
*
* Reading from /dev/random has the same functionality as calling
* getrandom(2) with flags=0. In earlier versions, however, it had
* vastly different semantics and should therefore be avoided, to
* prevent backwards compatibility issues.
*
* Reading from /dev/urandom has the same functionality as calling
* getrandom(2) with flags=GRND_INSECURE. Because it does not block
* waiting for the RNG to be ready, it should not be used.
*
* Writing to either /dev/random or /dev/urandom adds entropy to
* the input pool but does not credit it.
*
* Polling on /dev/random indicates when the RNG is initialized, on
* the read side, and when it wants new entropy, on the write side.
*
* Both /dev/random and /dev/urandom have the same set of ioctls for
* adding entropy, getting the entropy count, zeroing the count, and
* reseeding the crng.
*
**********************************************************************/
SYSCALL_DEFINE3(getrandom, char __user *, buf, size_t, count, unsigned int,
flags)
{
if (flags & ~(GRND_NONBLOCK | GRND_RANDOM | GRND_INSECURE))
return -EINVAL;
/*
* Requesting insecure and blocking randomness at the same time makes
* no sense.
*/
if ((flags & (GRND_INSECURE | GRND_RANDOM)) == (GRND_INSECURE | GRND_RANDOM))
return -EINVAL;
if (count > INT_MAX)
count = INT_MAX;
if (!(flags & GRND_INSECURE) && !crng_ready()) {
int ret;
if (flags & GRND_NONBLOCK)
return -EAGAIN;
ret = wait_for_random_bytes();
if (unlikely(ret))
return ret;
}
return get_random_bytes_user(buf, count);
}
static __poll_t random_poll(struct file *file, poll_table *wait)
{
__poll_t mask;
poll_wait(file, &crng_init_wait, wait);
poll_wait(file, &random_write_wait, wait);
mask = 0;
if (crng_ready())
mask |= EPOLLIN | EPOLLRDNORM;
if (input_pool.entropy_count < POOL_MIN_BITS)
mask |= EPOLLOUT | EPOLLWRNORM;
return mask;
}
static int write_pool(const char __user *ubuf, size_t count)
{
size_t len;
int ret = 0;
u8 block[BLAKE2S_BLOCK_SIZE];
while (count) {
len = min(count, sizeof(block));
if (copy_from_user(block, ubuf, len)) {
ret = -EFAULT;
goto out;
}
count -= len;
ubuf += len;
mix_pool_bytes(block, len);
cond_resched();
}
out:
memzero_explicit(block, sizeof(block));
return ret;
}
static ssize_t random_write(struct file *file, const char __user *buffer,
size_t count, loff_t *ppos)
{
int ret;
ret = write_pool(buffer, count);
if (ret)
return ret;
return (ssize_t)count;
}
static ssize_t urandom_read(struct file *file, char __user *buf, size_t nbytes,
loff_t *ppos)
{
static int maxwarn = 10;
if (!crng_ready() && maxwarn > 0) {
maxwarn--;
if (__ratelimit(&urandom_warning))
pr_notice("%s: uninitialized urandom read (%zd bytes read)\n",
current->comm, nbytes);
}
return get_random_bytes_user(buf, nbytes);
}
static ssize_t random_read(struct file *file, char __user *buf, size_t nbytes,
loff_t *ppos)
{
int ret;
ret = wait_for_random_bytes();
if (ret != 0)
return ret;
return get_random_bytes_user(buf, nbytes);
}
static long random_ioctl(struct file *f, unsigned int cmd, unsigned long arg)
{
int size, ent_count;
int __user *p = (int __user *)arg;
int retval;
switch (cmd) {
case RNDGETENTCNT:
/* Inherently racy, no point locking. */
random: use linear min-entropy accumulation crediting 30e37ec516ae ("random: account for entropy loss due to overwrites") assumed that adding new entropy to the LFSR pool probabilistically cancelled out old entropy there, so entropy was credited asymptotically, approximating Shannon entropy of independent sources (rather than a stronger min-entropy notion) using 1/8th fractional bits and replacing a constant 2-2/√𝑒 term (~0.786938) with 3/4 (0.75) to slightly underestimate it. This wasn't superb, but it was perhaps better than nothing, so that's what was done. Which entropy specifically was being cancelled out and how much precisely each time is hard to tell, though as I showed with the attack code in my previous commit, a motivated adversary with sufficient information can actually cancel out everything. Since we're no longer using an LFSR for entropy accumulation, this probabilistic cancellation is no longer relevant. Rather, we're now using a computational hash function as the accumulator and we've switched to working in the random oracle model, from which we can now revisit the question of min-entropy accumulation, which is done in detail in <https://eprint.iacr.org/2019/198>. Consider a long input bit string that is built by concatenating various smaller independent input bit strings. Each one of these inputs has a designated min-entropy, which is what we're passing to credit_entropy_bits(h). When we pass the concatenation of these to a random oracle, it means that an adversary trying to receive back the same reply as us would need to become certain about each part of the concatenated bit string we passed in, which means becoming certain about all of those h values. That means we can estimate the accumulation by simply adding up the h values in calls to credit_entropy_bits(h); there's no probabilistic cancellation at play like there was said to be for the LFSR. Incidentally, this is also what other entropy accumulators based on computational hash functions do as well. So this commit replaces credit_entropy_bits(h) with essentially `total = min(POOL_BITS, total + h)`, done with a cmpxchg loop as before. What if we're wrong and the above is nonsense? It's not, but let's assume we don't want the actual _behavior_ of the code to change much. Currently that behavior is not extracting from the input pool until it has 128 bits of entropy in it. With the old algorithm, we'd hit that magic 128 number after roughly 256 calls to credit_entropy_bits(1). So, we can retain more or less the old behavior by waiting to extract from the input pool until it hits 256 bits of entropy using the new code. For people concerned about this change, it means that there's not that much practical behavioral change. And for folks actually trying to model the behavior rigorously, it means that we have an even higher margin against attacks. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Reviewed-by: Eric Biggers <ebiggers@google.com> Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-03 12:28:06 +00:00
if (put_user(input_pool.entropy_count, p))
return -EFAULT;
return 0;
case RNDADDTOENTCNT:
if (!capable(CAP_SYS_ADMIN))
return -EPERM;
if (get_user(ent_count, p))
return -EFAULT;
if (ent_count < 0)
return -EINVAL;
credit_entropy_bits(ent_count);
return 0;
case RNDADDENTROPY:
if (!capable(CAP_SYS_ADMIN))
return -EPERM;
if (get_user(ent_count, p++))
return -EFAULT;
if (ent_count < 0)
return -EINVAL;
if (get_user(size, p++))
return -EFAULT;
retval = write_pool((const char __user *)p, size);
if (retval < 0)
return retval;
credit_entropy_bits(ent_count);
return 0;
case RNDZAPENTCNT:
case RNDCLEARPOOL:
/*
* Clear the entropy pool counters. We no longer clear
* the entropy pool, as that's silly.
*/
if (!capable(CAP_SYS_ADMIN))
return -EPERM;
if (xchg(&input_pool.entropy_count, 0) >= POOL_MIN_BITS) {
wake_up_interruptible(&random_write_wait);
kill_fasync(&fasync, SIGIO, POLL_OUT);
}
return 0;
case RNDRESEEDCRNG:
if (!capable(CAP_SYS_ADMIN))
return -EPERM;
if (!crng_ready())
return -ENODATA;
crng_reseed(false);
return 0;
default:
return -EINVAL;
}
}
2008-04-29 08:03:08 +00:00
static int random_fasync(int fd, struct file *filp, int on)
{
return fasync_helper(fd, filp, on, &fasync);
}
const struct file_operations random_fops = {
.read = random_read,
.write = random_write,
.poll = random_poll,
.unlocked_ioctl = random_ioctl,
.compat_ioctl = compat_ptr_ioctl,
2008-04-29 08:03:08 +00:00
.fasync = random_fasync,
llseek: automatically add .llseek fop All file_operations should get a .llseek operation so we can make nonseekable_open the default for future file operations without a .llseek pointer. The three cases that we can automatically detect are no_llseek, seq_lseek and default_llseek. For cases where we can we can automatically prove that the file offset is always ignored, we use noop_llseek, which maintains the current behavior of not returning an error from a seek. New drivers should normally not use noop_llseek but instead use no_llseek and call nonseekable_open at open time. Existing drivers can be converted to do the same when the maintainer knows for certain that no user code relies on calling seek on the device file. The generated code is often incorrectly indented and right now contains comments that clarify for each added line why a specific variant was chosen. In the version that gets submitted upstream, the comments will be gone and I will manually fix the indentation, because there does not seem to be a way to do that using coccinelle. Some amount of new code is currently sitting in linux-next that should get the same modifications, which I will do at the end of the merge window. Many thanks to Julia Lawall for helping me learn to write a semantic patch that does all this. ===== begin semantic patch ===== // This adds an llseek= method to all file operations, // as a preparation for making no_llseek the default. // // The rules are // - use no_llseek explicitly if we do nonseekable_open // - use seq_lseek for sequential files // - use default_llseek if we know we access f_pos // - use noop_llseek if we know we don't access f_pos, // but we still want to allow users to call lseek // @ open1 exists @ identifier nested_open; @@ nested_open(...) { <+... nonseekable_open(...) ...+> } @ open exists@ identifier open_f; identifier i, f; identifier open1.nested_open; @@ int open_f(struct inode *i, struct file *f) { <+... ( nonseekable_open(...) | nested_open(...) ) ...+> } @ read disable optional_qualifier exists @ identifier read_f; identifier f, p, s, off; type ssize_t, size_t, loff_t; expression E; identifier func; @@ ssize_t read_f(struct file *f, char *p, size_t s, loff_t *off) { <+... ( *off = E | *off += E | func(..., off, ...) | E = *off ) ...+> } @ read_no_fpos disable optional_qualifier exists @ identifier read_f; identifier f, p, s, off; type ssize_t, size_t, loff_t; @@ ssize_t read_f(struct file *f, char *p, size_t s, loff_t *off) { ... when != off } @ write @ identifier write_f; identifier f, p, s, off; type ssize_t, size_t, loff_t; expression E; identifier func; @@ ssize_t write_f(struct file *f, const char *p, size_t s, loff_t *off) { <+... ( *off = E | *off += E | func(..., off, ...) | E = *off ) ...+> } @ write_no_fpos @ identifier write_f; identifier f, p, s, off; type ssize_t, size_t, loff_t; @@ ssize_t write_f(struct file *f, const char *p, size_t s, loff_t *off) { ... when != off } @ fops0 @ identifier fops; @@ struct file_operations fops = { ... }; @ has_llseek depends on fops0 @ identifier fops0.fops; identifier llseek_f; @@ struct file_operations fops = { ... .llseek = llseek_f, ... }; @ has_read depends on fops0 @ identifier fops0.fops; identifier read_f; @@ struct file_operations fops = { ... .read = read_f, ... }; @ has_write depends on fops0 @ identifier fops0.fops; identifier write_f; @@ struct file_operations fops = { ... .write = write_f, ... }; @ has_open depends on fops0 @ identifier fops0.fops; identifier open_f; @@ struct file_operations fops = { ... .open = open_f, ... }; // use no_llseek if we call nonseekable_open //////////////////////////////////////////// @ nonseekable1 depends on !has_llseek && has_open @ identifier fops0.fops; identifier nso ~= "nonseekable_open"; @@ struct file_operations fops = { ... .open = nso, ... +.llseek = no_llseek, /* nonseekable */ }; @ nonseekable2 depends on !has_llseek @ identifier fops0.fops; identifier open.open_f; @@ struct file_operations fops = { ... .open = open_f, ... +.llseek = no_llseek, /* open uses nonseekable */ }; // use seq_lseek for sequential files ///////////////////////////////////// @ seq depends on !has_llseek @ identifier fops0.fops; identifier sr ~= "seq_read"; @@ struct file_operations fops = { ... .read = sr, ... +.llseek = seq_lseek, /* we have seq_read */ }; // use default_llseek if there is a readdir /////////////////////////////////////////// @ fops1 depends on !has_llseek && !nonseekable1 && !nonseekable2 && !seq @ identifier fops0.fops; identifier readdir_e; @@ // any other fop is used that changes pos struct file_operations fops = { ... .readdir = readdir_e, ... +.llseek = default_llseek, /* readdir is present */ }; // use default_llseek if at least one of read/write touches f_pos ///////////////////////////////////////////////////////////////// @ fops2 depends on !fops1 && !has_llseek && !nonseekable1 && !nonseekable2 && !seq @ identifier fops0.fops; identifier read.read_f; @@ // read fops use offset struct file_operations fops = { ... .read = read_f, ... +.llseek = default_llseek, /* read accesses f_pos */ }; @ fops3 depends on !fops1 && !fops2 && !has_llseek && !nonseekable1 && !nonseekable2 && !seq @ identifier fops0.fops; identifier write.write_f; @@ // write fops use offset struct file_operations fops = { ... .write = write_f, ... + .llseek = default_llseek, /* write accesses f_pos */ }; // Use noop_llseek if neither read nor write accesses f_pos /////////////////////////////////////////////////////////// @ fops4 depends on !fops1 && !fops2 && !fops3 && !has_llseek && !nonseekable1 && !nonseekable2 && !seq @ identifier fops0.fops; identifier read_no_fpos.read_f; identifier write_no_fpos.write_f; @@ // write fops use offset struct file_operations fops = { ... .write = write_f, .read = read_f, ... +.llseek = noop_llseek, /* read and write both use no f_pos */ }; @ depends on has_write && !has_read && !fops1 && !fops2 && !has_llseek && !nonseekable1 && !nonseekable2 && !seq @ identifier fops0.fops; identifier write_no_fpos.write_f; @@ struct file_operations fops = { ... .write = write_f, ... +.llseek = noop_llseek, /* write uses no f_pos */ }; @ depends on has_read && !has_write && !fops1 && !fops2 && !has_llseek && !nonseekable1 && !nonseekable2 && !seq @ identifier fops0.fops; identifier read_no_fpos.read_f; @@ struct file_operations fops = { ... .read = read_f, ... +.llseek = noop_llseek, /* read uses no f_pos */ }; @ depends on !has_read && !has_write && !fops1 && !fops2 && !has_llseek && !nonseekable1 && !nonseekable2 && !seq @ identifier fops0.fops; @@ struct file_operations fops = { ... +.llseek = noop_llseek, /* no read or write fn */ }; ===== End semantic patch ===== Signed-off-by: Arnd Bergmann <arnd@arndb.de> Cc: Julia Lawall <julia@diku.dk> Cc: Christoph Hellwig <hch@infradead.org>
2010-08-15 16:52:59 +00:00
.llseek = noop_llseek,
};
const struct file_operations urandom_fops = {
.read = urandom_read,
.write = random_write,
.unlocked_ioctl = random_ioctl,
.compat_ioctl = compat_ptr_ioctl,
.fasync = random_fasync,
.llseek = noop_llseek,
};
/********************************************************************
*
* Sysctl interface.
*
* These are partly unused legacy knobs with dummy values to not break
* userspace and partly still useful things. They are usually accessible
* in /proc/sys/kernel/random/ and are as follows:
*
* - boot_id - a UUID representing the current boot.
*
* - uuid - a random UUID, different each time the file is read.
*
* - poolsize - the number of bits of entropy that the input pool can
* hold, tied to the POOL_BITS constant.
*
* - entropy_avail - the number of bits of entropy currently in the
* input pool. Always <= poolsize.
*
* - write_wakeup_threshold - the amount of entropy in the input pool
* below which write polls to /dev/random will unblock, requesting
* more entropy, tied to the POOL_MIN_BITS constant. It is writable
* to avoid breaking old userspaces, but writing to it does not
* change any behavior of the RNG.
*
* - urandom_min_reseed_secs - fixed to the value CRNG_RESEED_INTERVAL.
* It is writable to avoid breaking old userspaces, but writing
* to it does not change any behavior of the RNG.
*
********************************************************************/
#ifdef CONFIG_SYSCTL
#include <linux/sysctl.h>
static int sysctl_random_min_urandom_seed = CRNG_RESEED_INTERVAL / HZ;
static int sysctl_random_write_wakeup_bits = POOL_MIN_BITS;
static int sysctl_poolsize = POOL_BITS;
static u8 sysctl_bootid[UUID_SIZE];
/*
* This function is used to return both the bootid UUID, and random
* UUID. The difference is in whether table->data is NULL; if it is,
* then a new UUID is generated and returned to the user.
*/
static int proc_do_uuid(struct ctl_table *table, int write, void *buffer,
size_t *lenp, loff_t *ppos)
{
u8 tmp_uuid[UUID_SIZE], *uuid;
char uuid_string[UUID_STRING_LEN + 1];
struct ctl_table fake_table = {
.data = uuid_string,
.maxlen = UUID_STRING_LEN
};
if (write)
return -EPERM;
uuid = table->data;
if (!uuid) {
uuid = tmp_uuid;
generate_random_uuid(uuid);
} else {
static DEFINE_SPINLOCK(bootid_spinlock);
spin_lock(&bootid_spinlock);
if (!uuid[8])
generate_random_uuid(uuid);
spin_unlock(&bootid_spinlock);
}
snprintf(uuid_string, sizeof(uuid_string), "%pU", uuid);
return proc_dostring(&fake_table, 0, buffer, lenp, ppos);
}
/* The same as proc_dointvec, but writes don't change anything. */
static int proc_do_rointvec(struct ctl_table *table, int write, void *buffer,
size_t *lenp, loff_t *ppos)
{
return write ? 0 : proc_dointvec(table, 0, buffer, lenp, ppos);
}
random: move the random sysctl declarations to its own file kernel/sysctl.c is a kitchen sink where everyone leaves their dirty dishes, this makes it very difficult to maintain. To help with this maintenance let's start by moving sysctls to places where they actually belong. The proc sysctl maintainers do not want to know what sysctl knobs you wish to add for your own piece of code, we just care about the core logic. So move the random sysctls to their own file and use register_sysctl_init(). [mcgrof@kernel.org: commit log update to justify the move] Link: https://lkml.kernel.org/r/20211124231435.1445213-3-mcgrof@kernel.org Signed-off-by: Xiaoming Ni <nixiaoming@huawei.com> Signed-off-by: Luis Chamberlain <mcgrof@kernel.org> Cc: Al Viro <viro@zeniv.linux.org.uk> Cc: Amir Goldstein <amir73il@gmail.com> Cc: Andy Shevchenko <andriy.shevchenko@linux.intel.com> Cc: Antti Palosaari <crope@iki.fi> Cc: Arnd Bergmann <arnd@arndb.de> Cc: Benjamin Herrenschmidt <benh@kernel.crashing.org> Cc: Benjamin LaHaise <bcrl@kvack.org> Cc: Clemens Ladisch <clemens@ladisch.de> Cc: David Airlie <airlied@linux.ie> Cc: Douglas Gilbert <dgilbert@interlog.com> Cc: Eric Biederman <ebiederm@xmission.com> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Cc: Iurii Zaikin <yzaikin@google.com> Cc: James E.J. Bottomley <jejb@linux.ibm.com> Cc: Jani Nikula <jani.nikula@intel.com> Cc: Jani Nikula <jani.nikula@linux.intel.com> Cc: Jan Kara <jack@suse.cz> Cc: Joel Becker <jlbec@evilplan.org> Cc: John Ogness <john.ogness@linutronix.de> Cc: Joonas Lahtinen <joonas.lahtinen@linux.intel.com> Cc: Joseph Qi <joseph.qi@linux.alibaba.com> Cc: Julia Lawall <julia.lawall@inria.fr> Cc: Kees Cook <keescook@chromium.org> Cc: Lukas Middendorf <kernel@tuxforce.de> Cc: Mark Fasheh <mark@fasheh.com> Cc: Martin K. Petersen <martin.petersen@oracle.com> Cc: Paul Turner <pjt@google.com> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Petr Mladek <pmladek@suse.com> Cc: Phillip Potter <phil@philpotter.co.uk> Cc: Qing Wang <wangqing@vivo.com> Cc: "Rafael J. Wysocki" <rafael@kernel.org> Cc: Rodrigo Vivi <rodrigo.vivi@intel.com> Cc: Sebastian Reichel <sre@kernel.org> Cc: Sergey Senozhatsky <senozhatsky@chromium.org> Cc: Stephen Kitt <steve@sk2.org> Cc: Steven Rostedt (VMware) <rostedt@goodmis.org> Cc: Suren Baghdasaryan <surenb@google.com> Cc: Tetsuo Handa <penguin-kernel@I-love.SAKURA.ne.jp> Cc: "Theodore Ts'o" <tytso@mit.edu> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2022-01-22 06:12:18 +00:00
static struct ctl_table random_table[] = {
{
.procname = "poolsize",
.data = &sysctl_poolsize,
.maxlen = sizeof(int),
.mode = 0444,
.proc_handler = proc_dointvec,
},
{
.procname = "entropy_avail",
random: use linear min-entropy accumulation crediting 30e37ec516ae ("random: account for entropy loss due to overwrites") assumed that adding new entropy to the LFSR pool probabilistically cancelled out old entropy there, so entropy was credited asymptotically, approximating Shannon entropy of independent sources (rather than a stronger min-entropy notion) using 1/8th fractional bits and replacing a constant 2-2/√𝑒 term (~0.786938) with 3/4 (0.75) to slightly underestimate it. This wasn't superb, but it was perhaps better than nothing, so that's what was done. Which entropy specifically was being cancelled out and how much precisely each time is hard to tell, though as I showed with the attack code in my previous commit, a motivated adversary with sufficient information can actually cancel out everything. Since we're no longer using an LFSR for entropy accumulation, this probabilistic cancellation is no longer relevant. Rather, we're now using a computational hash function as the accumulator and we've switched to working in the random oracle model, from which we can now revisit the question of min-entropy accumulation, which is done in detail in <https://eprint.iacr.org/2019/198>. Consider a long input bit string that is built by concatenating various smaller independent input bit strings. Each one of these inputs has a designated min-entropy, which is what we're passing to credit_entropy_bits(h). When we pass the concatenation of these to a random oracle, it means that an adversary trying to receive back the same reply as us would need to become certain about each part of the concatenated bit string we passed in, which means becoming certain about all of those h values. That means we can estimate the accumulation by simply adding up the h values in calls to credit_entropy_bits(h); there's no probabilistic cancellation at play like there was said to be for the LFSR. Incidentally, this is also what other entropy accumulators based on computational hash functions do as well. So this commit replaces credit_entropy_bits(h) with essentially `total = min(POOL_BITS, total + h)`, done with a cmpxchg loop as before. What if we're wrong and the above is nonsense? It's not, but let's assume we don't want the actual _behavior_ of the code to change much. Currently that behavior is not extracting from the input pool until it has 128 bits of entropy in it. With the old algorithm, we'd hit that magic 128 number after roughly 256 calls to credit_entropy_bits(1). So, we can retain more or less the old behavior by waiting to extract from the input pool until it hits 256 bits of entropy using the new code. For people concerned about this change, it means that there's not that much practical behavioral change. And for folks actually trying to model the behavior rigorously, it means that we have an even higher margin against attacks. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Reviewed-by: Eric Biggers <ebiggers@google.com> Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-03 12:28:06 +00:00
.data = &input_pool.entropy_count,
.maxlen = sizeof(int),
.mode = 0444,
random: use linear min-entropy accumulation crediting 30e37ec516ae ("random: account for entropy loss due to overwrites") assumed that adding new entropy to the LFSR pool probabilistically cancelled out old entropy there, so entropy was credited asymptotically, approximating Shannon entropy of independent sources (rather than a stronger min-entropy notion) using 1/8th fractional bits and replacing a constant 2-2/√𝑒 term (~0.786938) with 3/4 (0.75) to slightly underestimate it. This wasn't superb, but it was perhaps better than nothing, so that's what was done. Which entropy specifically was being cancelled out and how much precisely each time is hard to tell, though as I showed with the attack code in my previous commit, a motivated adversary with sufficient information can actually cancel out everything. Since we're no longer using an LFSR for entropy accumulation, this probabilistic cancellation is no longer relevant. Rather, we're now using a computational hash function as the accumulator and we've switched to working in the random oracle model, from which we can now revisit the question of min-entropy accumulation, which is done in detail in <https://eprint.iacr.org/2019/198>. Consider a long input bit string that is built by concatenating various smaller independent input bit strings. Each one of these inputs has a designated min-entropy, which is what we're passing to credit_entropy_bits(h). When we pass the concatenation of these to a random oracle, it means that an adversary trying to receive back the same reply as us would need to become certain about each part of the concatenated bit string we passed in, which means becoming certain about all of those h values. That means we can estimate the accumulation by simply adding up the h values in calls to credit_entropy_bits(h); there's no probabilistic cancellation at play like there was said to be for the LFSR. Incidentally, this is also what other entropy accumulators based on computational hash functions do as well. So this commit replaces credit_entropy_bits(h) with essentially `total = min(POOL_BITS, total + h)`, done with a cmpxchg loop as before. What if we're wrong and the above is nonsense? It's not, but let's assume we don't want the actual _behavior_ of the code to change much. Currently that behavior is not extracting from the input pool until it has 128 bits of entropy in it. With the old algorithm, we'd hit that magic 128 number after roughly 256 calls to credit_entropy_bits(1). So, we can retain more or less the old behavior by waiting to extract from the input pool until it hits 256 bits of entropy using the new code. For people concerned about this change, it means that there's not that much practical behavioral change. And for folks actually trying to model the behavior rigorously, it means that we have an even higher margin against attacks. Cc: Theodore Ts'o <tytso@mit.edu> Cc: Dominik Brodowski <linux@dominikbrodowski.net> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Reviewed-by: Eric Biggers <ebiggers@google.com> Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com> Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-03 12:28:06 +00:00
.proc_handler = proc_dointvec,
},
{
.procname = "write_wakeup_threshold",
.data = &sysctl_random_write_wakeup_bits,
.maxlen = sizeof(int),
.mode = 0644,
.proc_handler = proc_do_rointvec,
},
{
.procname = "urandom_min_reseed_secs",
.data = &sysctl_random_min_urandom_seed,
.maxlen = sizeof(int),
.mode = 0644,
.proc_handler = proc_do_rointvec,
},
{
.procname = "boot_id",
.data = &sysctl_bootid,
.mode = 0444,
.proc_handler = proc_do_uuid,
},
{
.procname = "uuid",
.mode = 0444,
.proc_handler = proc_do_uuid,
},
{ }
};
random: move the random sysctl declarations to its own file kernel/sysctl.c is a kitchen sink where everyone leaves their dirty dishes, this makes it very difficult to maintain. To help with this maintenance let's start by moving sysctls to places where they actually belong. The proc sysctl maintainers do not want to know what sysctl knobs you wish to add for your own piece of code, we just care about the core logic. So move the random sysctls to their own file and use register_sysctl_init(). [mcgrof@kernel.org: commit log update to justify the move] Link: https://lkml.kernel.org/r/20211124231435.1445213-3-mcgrof@kernel.org Signed-off-by: Xiaoming Ni <nixiaoming@huawei.com> Signed-off-by: Luis Chamberlain <mcgrof@kernel.org> Cc: Al Viro <viro@zeniv.linux.org.uk> Cc: Amir Goldstein <amir73il@gmail.com> Cc: Andy Shevchenko <andriy.shevchenko@linux.intel.com> Cc: Antti Palosaari <crope@iki.fi> Cc: Arnd Bergmann <arnd@arndb.de> Cc: Benjamin Herrenschmidt <benh@kernel.crashing.org> Cc: Benjamin LaHaise <bcrl@kvack.org> Cc: Clemens Ladisch <clemens@ladisch.de> Cc: David Airlie <airlied@linux.ie> Cc: Douglas Gilbert <dgilbert@interlog.com> Cc: Eric Biederman <ebiederm@xmission.com> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Cc: Iurii Zaikin <yzaikin@google.com> Cc: James E.J. Bottomley <jejb@linux.ibm.com> Cc: Jani Nikula <jani.nikula@intel.com> Cc: Jani Nikula <jani.nikula@linux.intel.com> Cc: Jan Kara <jack@suse.cz> Cc: Joel Becker <jlbec@evilplan.org> Cc: John Ogness <john.ogness@linutronix.de> Cc: Joonas Lahtinen <joonas.lahtinen@linux.intel.com> Cc: Joseph Qi <joseph.qi@linux.alibaba.com> Cc: Julia Lawall <julia.lawall@inria.fr> Cc: Kees Cook <keescook@chromium.org> Cc: Lukas Middendorf <kernel@tuxforce.de> Cc: Mark Fasheh <mark@fasheh.com> Cc: Martin K. Petersen <martin.petersen@oracle.com> Cc: Paul Turner <pjt@google.com> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Petr Mladek <pmladek@suse.com> Cc: Phillip Potter <phil@philpotter.co.uk> Cc: Qing Wang <wangqing@vivo.com> Cc: "Rafael J. Wysocki" <rafael@kernel.org> Cc: Rodrigo Vivi <rodrigo.vivi@intel.com> Cc: Sebastian Reichel <sre@kernel.org> Cc: Sergey Senozhatsky <senozhatsky@chromium.org> Cc: Stephen Kitt <steve@sk2.org> Cc: Steven Rostedt (VMware) <rostedt@goodmis.org> Cc: Suren Baghdasaryan <surenb@google.com> Cc: Tetsuo Handa <penguin-kernel@I-love.SAKURA.ne.jp> Cc: "Theodore Ts'o" <tytso@mit.edu> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2022-01-22 06:12:18 +00:00
/*
* rand_initialize() is called before sysctl_init(),
* so we cannot call register_sysctl_init() in rand_initialize()
*/
static int __init random_sysctls_init(void)
{
register_sysctl_init("kernel/random", random_table);
return 0;
}
device_initcall(random_sysctls_init);
#endif