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bitcoin-bitcoin-core/src/random.h
fanquake 1e0198b6c1
Merge bitcoin/bitcoin#26153: Reduce wasted pseudorandom bytes in ChaCha20 + various improvements
511aa4f1c7 Add unit test for ChaCha20's new caching (Pieter Wuille)
fb243d25f7 Improve test vectors for ChaCha20 (Pieter Wuille)
93aee8bbda Inline ChaCha20 32-byte specific constants (Pieter Wuille)
62ec713961 Only support 32-byte keys in ChaCha20{,Aligned} (Pieter Wuille)
f21994a02e Use ChaCha20Aligned in MuHash3072 code (Pieter Wuille)
5d16f75763 Use ChaCha20 caching in FastRandomContext (Pieter Wuille)
38eaece67b Add fuzz test for testing that ChaCha20 works as a stream (Pieter Wuille)
5f05b27841 Add xoroshiro128++ PRNG (Martin Leitner-Ankerl)
12ff72476a Make unrestricted ChaCha20 cipher not waste keystream bytes (Pieter Wuille)
6babf40213 Rename ChaCha20::Seek -> Seek64 to clarify multiple of 64 (Pieter Wuille)
e37bcaa0a6 Split ChaCha20 into aligned/unaligned variants (Pieter Wuille)

Pull request description:

  This is an alternative to #25354 (by my benchmarking, somewhat faster), subsumes #25712, and adds additional test vectors.

  It separates the multiple-of-64-bytes-only "core" logic (which becomes simpler) from a layer around which performs caching/slicing to support arbitrary byte amounts. Both have their uses (in particular, the MuHash3072 code can benefit from multiple-of-64-bytes assumptions), plus the separation results in more readable code. Also, since FastRandomContext effectively had its own (more naive) caching on top of ChaCha20, that can be dropped in favor of ChaCha20's new built-in caching.

  I thought about rebasing #25712 on top of this, but the changes before are fairly extensive, so redid it instead.

ACKs for top commit:
  ajtowns:
    ut reACK 511aa4f1c7
  dhruv:
    tACK crACK 511aa4f1c7

Tree-SHA512: 3aa80971322a93e780c75a8d35bd39da3a9ea570fbae4491eaf0c45242f5f670a24a592c50ad870d5fd09b9f88ec06e274e8aa3cefd9561d623c63f7198cf2c7
2023-02-15 14:58:47 +00:00

297 lines
11 KiB
C++

// Copyright (c) 2009-2010 Satoshi Nakamoto
// Copyright (c) 2009-2022 The Bitcoin Core developers
// Distributed under the MIT software license, see the accompanying
// file COPYING or http://www.opensource.org/licenses/mit-license.php.
#ifndef BITCOIN_RANDOM_H
#define BITCOIN_RANDOM_H
#include <crypto/chacha20.h>
#include <crypto/common.h>
#include <span.h>
#include <uint256.h>
#include <cassert>
#include <chrono>
#include <cstdint>
#include <limits>
#include <vector>
/**
* Overall design of the RNG and entropy sources.
*
* We maintain a single global 256-bit RNG state for all high-quality randomness.
* The following (classes of) functions interact with that state by mixing in new
* entropy, and optionally extracting random output from it:
*
* - The GetRand*() class of functions, as well as construction of FastRandomContext objects,
* perform 'fast' seeding, consisting of mixing in:
* - A stack pointer (indirectly committing to calling thread and call stack)
* - A high-precision timestamp (rdtsc when available, c++ high_resolution_clock otherwise)
* - 64 bits from the hardware RNG (rdrand) when available.
* These entropy sources are very fast, and only designed to protect against situations
* where a VM state restore/copy results in multiple systems with the same randomness.
* FastRandomContext on the other hand does not protect against this once created, but
* is even faster (and acceptable to use inside tight loops).
*
* - The GetStrongRand*() class of function perform 'slow' seeding, including everything
* that fast seeding includes, but additionally:
* - OS entropy (/dev/urandom, getrandom(), ...). The application will terminate if
* this entropy source fails.
* - Another high-precision timestamp (indirectly committing to a benchmark of all the
* previous sources).
* These entropy sources are slower, but designed to make sure the RNG state contains
* fresh data that is unpredictable to attackers.
*
* - RandAddPeriodic() seeds everything that fast seeding includes, but additionally:
* - A high-precision timestamp
* - Dynamic environment data (performance monitoring, ...)
* - Strengthen the entropy for 10 ms using repeated SHA512.
* This is run once every minute.
*
* On first use of the RNG (regardless of what function is called first), all entropy
* sources used in the 'slow' seeder are included, but also:
* - 256 bits from the hardware RNG (rdseed or rdrand) when available.
* - Dynamic environment data (performance monitoring, ...)
* - Static environment data
* - Strengthen the entropy for 100 ms using repeated SHA512.
*
* When mixing in new entropy, H = SHA512(entropy || old_rng_state) is computed, and
* (up to) the first 32 bytes of H are produced as output, while the last 32 bytes
* become the new RNG state.
*/
/**
* Generate random data via the internal PRNG.
*
* These functions are designed to be fast (sub microsecond), but do not necessarily
* meaningfully add entropy to the PRNG state.
*
* Thread-safe.
*/
void GetRandBytes(Span<unsigned char> bytes) noexcept;
/** Generate a uniform random integer in the range [0..range). Precondition: range > 0 */
uint64_t GetRandInternal(uint64_t nMax) noexcept;
/** Generate a uniform random integer of type T in the range [0..nMax)
* nMax defaults to std::numeric_limits<T>::max()
* Precondition: nMax > 0, T is an integral type, no larger than uint64_t
*/
template<typename T>
T GetRand(T nMax=std::numeric_limits<T>::max()) noexcept {
static_assert(std::is_integral<T>(), "T must be integral");
static_assert(std::numeric_limits<T>::max() <= std::numeric_limits<uint64_t>::max(), "GetRand only supports up to uint64_t");
return T(GetRandInternal(nMax));
}
/** Generate a uniform random duration in the range [0..max). Precondition: max.count() > 0 */
template <typename D>
D GetRandomDuration(typename std::common_type<D>::type max) noexcept
// Having the compiler infer the template argument from the function argument
// is dangerous, because the desired return value generally has a different
// type than the function argument. So std::common_type is used to force the
// call site to specify the type of the return value.
{
assert(max.count() > 0);
return D{GetRand(max.count())};
};
constexpr auto GetRandMicros = GetRandomDuration<std::chrono::microseconds>;
constexpr auto GetRandMillis = GetRandomDuration<std::chrono::milliseconds>;
/**
* Return a timestamp in the future sampled from an exponential distribution
* (https://en.wikipedia.org/wiki/Exponential_distribution). This distribution
* is memoryless and should be used for repeated network events (e.g. sending a
* certain type of message) to minimize leaking information to observers.
*
* The probability of an event occurring before time x is 1 - e^-(x/a) where a
* is the average interval between events.
* */
std::chrono::microseconds GetExponentialRand(std::chrono::microseconds now, std::chrono::seconds average_interval);
uint256 GetRandHash() noexcept;
/**
* Gather entropy from various sources, feed it into the internal PRNG, and
* generate random data using it.
*
* This function will cause failure whenever the OS RNG fails.
*
* Thread-safe.
*/
void GetStrongRandBytes(Span<unsigned char> bytes) noexcept;
/**
* Gather entropy from various expensive sources, and feed them to the PRNG state.
*
* Thread-safe.
*/
void RandAddPeriodic() noexcept;
/**
* Gathers entropy from the low bits of the time at which events occur. Should
* be called with a uint32_t describing the event at the time an event occurs.
*
* Thread-safe.
*/
void RandAddEvent(const uint32_t event_info) noexcept;
/**
* Fast randomness source. This is seeded once with secure random data, but
* is completely deterministic and does not gather more entropy after that.
*
* This class is not thread-safe.
*/
class FastRandomContext
{
private:
bool requires_seed;
ChaCha20 rng;
uint64_t bitbuf;
int bitbuf_size;
void RandomSeed();
void FillBitBuffer()
{
bitbuf = rand64();
bitbuf_size = 64;
}
public:
explicit FastRandomContext(bool fDeterministic = false) noexcept;
/** Initialize with explicit seed (only for testing) */
explicit FastRandomContext(const uint256& seed) noexcept;
// Do not permit copying a FastRandomContext (move it, or create a new one to get reseeded).
FastRandomContext(const FastRandomContext&) = delete;
FastRandomContext(FastRandomContext&&) = delete;
FastRandomContext& operator=(const FastRandomContext&) = delete;
/** Move a FastRandomContext. If the original one is used again, it will be reseeded. */
FastRandomContext& operator=(FastRandomContext&& from) noexcept;
/** Generate a random 64-bit integer. */
uint64_t rand64() noexcept
{
if (requires_seed) RandomSeed();
unsigned char buf[8];
rng.Keystream(buf, 8);
return ReadLE64(buf);
}
/** Generate a random (bits)-bit integer. */
uint64_t randbits(int bits) noexcept
{
if (bits == 0) {
return 0;
} else if (bits > 32) {
return rand64() >> (64 - bits);
} else {
if (bitbuf_size < bits) FillBitBuffer();
uint64_t ret = bitbuf & (~uint64_t{0} >> (64 - bits));
bitbuf >>= bits;
bitbuf_size -= bits;
return ret;
}
}
/** Generate a random integer in the range [0..range).
* Precondition: range > 0.
*/
uint64_t randrange(uint64_t range) noexcept
{
assert(range);
--range;
int bits = CountBits(range);
while (true) {
uint64_t ret = randbits(bits);
if (ret <= range) return ret;
}
}
/** Generate random bytes. */
std::vector<unsigned char> randbytes(size_t len);
/** Generate a random 32-bit integer. */
uint32_t rand32() noexcept { return randbits(32); }
/** generate a random uint256. */
uint256 rand256() noexcept;
/** Generate a random boolean. */
bool randbool() noexcept { return randbits(1); }
/** Return the time point advanced by a uniform random duration. */
template <typename Tp>
Tp rand_uniform_delay(const Tp& time, typename Tp::duration range)
{
return time + rand_uniform_duration<Tp>(range);
}
/** Generate a uniform random duration in the range from 0 (inclusive) to range (exclusive). */
template <typename Chrono>
typename Chrono::duration rand_uniform_duration(typename Chrono::duration range) noexcept
{
using Dur = typename Chrono::duration;
return range.count() > 0 ? /* interval [0..range) */ Dur{randrange(range.count())} :
range.count() < 0 ? /* interval (range..0] */ -Dur{randrange(-range.count())} :
/* interval [0..0] */ Dur{0};
};
// Compatibility with the UniformRandomBitGenerator concept
typedef uint64_t result_type;
static constexpr uint64_t min() { return 0; }
static constexpr uint64_t max() { return std::numeric_limits<uint64_t>::max(); }
inline uint64_t operator()() noexcept { return rand64(); }
};
/** More efficient than using std::shuffle on a FastRandomContext.
*
* This is more efficient as std::shuffle will consume entropy in groups of
* 64 bits at the time and throw away most.
*
* This also works around a bug in libstdc++ std::shuffle that may cause
* type::operator=(type&&) to be invoked on itself, which the library's
* debug mode detects and panics on. This is a known issue, see
* https://stackoverflow.com/questions/22915325/avoiding-self-assignment-in-stdshuffle
*/
template <typename I, typename R>
void Shuffle(I first, I last, R&& rng)
{
while (first != last) {
size_t j = rng.randrange(last - first);
if (j) {
using std::swap;
swap(*first, *(first + j));
}
++first;
}
}
/* Number of random bytes returned by GetOSRand.
* When changing this constant make sure to change all call sites, and make
* sure that the underlying OS APIs for all platforms support the number.
* (many cap out at 256 bytes).
*/
static const int NUM_OS_RANDOM_BYTES = 32;
/** Get 32 bytes of system entropy. Do not use this in application code: use
* GetStrongRandBytes instead.
*/
void GetOSRand(unsigned char* ent32);
/** Check that OS randomness is available and returning the requested number
* of bytes.
*/
bool Random_SanityCheck();
/**
* Initialize global RNG state and log any CPU features that are used.
*
* Calling this function is optional. RNG state will be initialized when first
* needed if it is not called.
*/
void RandomInit();
#endif // BITCOIN_RANDOM_H