// Copyright (c) 2009-2010 Satoshi Nakamoto // Copyright (c) 2009-2020 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 #include #include #include #include #include // For std::chrono::microseconds #include #include #include /** * 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 bytes) noexcept; /** Generate a uniform random integer in the range [0..range). Precondition: range > 0 */ uint64_t GetRand(uint64_t nMax) noexcept; /** Generate a uniform random duration in the range [0..max). Precondition: max.count() > 0 */ template D GetRandomDuration(typename std::common_type::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; constexpr auto GetRandMillis = GetRandomDuration; /** * 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 occuring 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); int GetRandInt(int nMax) noexcept; uint256 GetRandHash() noexcept; bool GetRandBool(double rate); /** * 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 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(); std::array buf; rng.Keystream(buf); return ReadLE64(UCharCast(buf.data())); } /** 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; } } uint32_t rand32(uint32_t nMax) { return rand32() % nMax; } /** Generate random bytes. */ template std::vector randbytes(size_t len); /** Fill a byte Span with random bytes. */ void fillrand(Span output); /** 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 Tp rand_uniform_delay(const Tp& time, typename Tp::duration range) { return time + rand_uniform_duration(range); } /** Generate a uniform random duration in the range from 0 (inclusive) to range (exclusive). */ template 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::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 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