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diff --git a/rand/src/jitter.rs b/rand/src/jitter.rs new file mode 100644 index 0000000..3693481 --- /dev/null +++ b/rand/src/jitter.rs @@ -0,0 +1,754 @@ +// Copyright 2017 The Rust Project Developers. See the COPYRIGHT +// file at the top-level directory of this distribution and at +// http://rust-lang.org/COPYRIGHT. +// +// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or +// http://www.apache.org/licenses/LICENSE-2.0> or the MIT license +// <LICENSE-MIT or http://opensource.org/licenses/MIT>, at your +// option. This file may not be copied, modified, or distributed +// except according to those terms. +// +// Based on jitterentropy-library, http://www.chronox.de/jent.html. +// Copyright Stephan Mueller <smueller@chronox.de>, 2014 - 2017. +// +// With permission from Stephan Mueller to relicense the Rust translation under +// the MIT license. + +//! Non-physical true random number generator based on timing jitter. + +use Rng; + +use core::{fmt, mem, ptr}; +#[cfg(feature="std")] +use std::sync::atomic::{AtomicUsize, ATOMIC_USIZE_INIT, Ordering}; + +const MEMORY_BLOCKS: usize = 64; +const MEMORY_BLOCKSIZE: usize = 32; +const MEMORY_SIZE: usize = MEMORY_BLOCKS * MEMORY_BLOCKSIZE; + +/// A true random number generator based on jitter in the CPU execution time, +/// and jitter in memory access time. +/// +/// This is a true random number generator, as opposed to pseudo-random +/// generators. Random numbers generated by `JitterRng` can be seen as fresh +/// entropy. A consequence is that is orders of magnitude slower than `OsRng` +/// and PRNGs (about 10^3 .. 10^6 slower). +/// +/// There are very few situations where using this RNG is appropriate. Only very +/// few applications require true entropy. A normal PRNG can be statistically +/// indistinguishable, and a cryptographic PRNG should also be as impossible to +/// predict. +/// +/// Use of `JitterRng` is recommended for initializing cryptographic PRNGs when +/// `OsRng` is not available. +/// +/// This implementation is based on +/// [Jitterentropy](http://www.chronox.de/jent.html) version 2.1.0. +// +// Note: the C implementation relies on being compiled without optimizations. +// This implementation goes through lengths to make the compiler not optimise +// out what is technically dead code, but that does influence timing jitter. +pub struct JitterRng { + data: u64, // Actual random number + // Number of rounds to run the entropy collector per 64 bits + rounds: u32, + // Timer and previous time stamp, used by `measure_jitter` + timer: fn() -> u64, + prev_time: u64, + // Deltas used for the stuck test + last_delta: i64, + last_delta2: i64, + // Memory for the Memory Access noise source + mem_prev_index: usize, + mem: [u8; MEMORY_SIZE], + // Make `next_u32` not waste 32 bits + data_remaining: Option<u32>, +} + +// Custom Debug implementation that does not expose the internal state +impl fmt::Debug for JitterRng { + fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result { + write!(f, "JitterRng {{}}") + } +} + +/// An error that can occur when `test_timer` fails. +#[derive(Debug, Clone, PartialEq, Eq)] +pub enum TimerError { + /// No timer available. + NoTimer, + /// Timer too coarse to use as an entropy source. + CoarseTimer, + /// Timer is not monotonically increasing. + NotMonotonic, + /// Variations of deltas of time too small. + TinyVariantions, + /// Too many stuck results (indicating no added entropy). + TooManyStuck, + #[doc(hidden)] + __Nonexhaustive, +} + +impl TimerError { + fn description(&self) -> &'static str { + match *self { + TimerError::NoTimer => "no timer available", + TimerError::CoarseTimer => "coarse timer", + TimerError::NotMonotonic => "timer not monotonic", + TimerError::TinyVariantions => "time delta variations too small", + TimerError::TooManyStuck => "too many stuck results", + TimerError::__Nonexhaustive => unreachable!(), + } + } +} + +impl fmt::Display for TimerError { + fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result { + write!(f, "{}", self.description()) + } +} + +#[cfg(feature="std")] +impl ::std::error::Error for TimerError { + fn description(&self) -> &str { + self.description() + } +} + +// Initialise to zero; must be positive +#[cfg(feature="std")] +static JITTER_ROUNDS: AtomicUsize = ATOMIC_USIZE_INIT; + +impl JitterRng { + /// Create a new `JitterRng`. + /// Makes use of `std::time` for a timer. + /// + /// During initialization CPU execution timing jitter is measured a few + /// hundred times. If this does not pass basic quality tests, an error is + /// returned. The test result is cached to make subsequent calls faster. + #[cfg(feature="std")] + pub fn new() -> Result<JitterRng, TimerError> { + let mut ec = JitterRng::new_with_timer(platform::get_nstime); + let mut rounds = JITTER_ROUNDS.load(Ordering::Relaxed) as u32; + if rounds == 0 { + // No result yet: run test. + // This allows the timer test to run multiple times; we don't care. + rounds = ec.test_timer()?; + JITTER_ROUNDS.store(rounds as usize, Ordering::Relaxed); + } + ec.set_rounds(rounds); + Ok(ec) + } + + /// Create a new `JitterRng`. + /// A custom timer can be supplied, making it possible to use `JitterRng` in + /// `no_std` environments. + /// + /// The timer must have nanosecond precision. + /// + /// This method is more low-level than `new()`. It is the responsibility of + /// the caller to run `test_timer` before using any numbers generated with + /// `JitterRng`, and optionally call `set_rounds()`. + pub fn new_with_timer(timer: fn() -> u64) -> JitterRng { + let mut ec = JitterRng { + data: 0, + rounds: 64, + timer: timer, + prev_time: 0, + last_delta: 0, + last_delta2: 0, + mem_prev_index: 0, + mem: [0; MEMORY_SIZE], + data_remaining: None, + }; + + // Fill `data`, `prev_time`, `last_delta` and `last_delta2` with + // non-zero values. + ec.prev_time = timer(); + ec.gen_entropy(); + + // Do a single read from `self.mem` to make sure the Memory Access noise + // source is not optimised out. + // Note: this read is important, it effects optimisations for the entire + // module! + black_box(ec.mem[0]); + + ec + } + + /// Configures how many rounds are used to generate each 64-bit value. + /// This must be greater than zero, and has a big impact on performance + /// and output quality. + /// + /// `new_with_timer` conservatively uses 64 rounds, but often less rounds + /// can be used. The `test_timer()` function returns the minimum number of + /// rounds required for full strength (platform dependent), so one may use + /// `rng.set_rounds(rng.test_timer()?);` or cache the value. + pub fn set_rounds(&mut self, rounds: u32) { + assert!(rounds > 0); + self.rounds = rounds; + } + + // Calculate a random loop count used for the next round of an entropy + // collection, based on bits from a fresh value from the timer. + // + // The timer is folded to produce a number that contains at most `n_bits` + // bits. + // + // Note: A constant should be added to the resulting random loop count to + // prevent loops that run 0 times. + #[inline(never)] + fn random_loop_cnt(&mut self, n_bits: u32) -> u32 { + let mut rounds = 0; + + let mut time = (self.timer)(); + // Mix with the current state of the random number balance the random + // loop counter a bit more. + time ^= self.data; + + // We fold the time value as much as possible to ensure that as many + // bits of the time stamp are included as possible. + let folds = (64 + n_bits - 1) / n_bits; + let mask = (1 << n_bits) - 1; + for _ in 0..folds { + rounds ^= time & mask; + time = time >> n_bits; + } + + rounds as u32 + } + + // CPU jitter noise source + // Noise source based on the CPU execution time jitter + // + // This function injects the individual bits of the time value into the + // entropy pool using an LFSR. + // + // The code is deliberately inefficient with respect to the bit shifting. + // This function not only acts as folding operation, but this function's + // execution is used to measure the CPU execution time jitter. Any change to + // the loop in this function implies that careful retesting must be done. + #[inline(never)] + fn lfsr_time(&mut self, time: u64, var_rounds: bool) { + fn lfsr(mut data: u64, time: u64) -> u64{ + for i in 1..65 { + let mut tmp = time << (64 - i); + tmp = tmp >> (64 - 1); + + // Fibonacci LSFR with polynomial of + // x^64 + x^61 + x^56 + x^31 + x^28 + x^23 + 1 which is + // primitive according to + // http://poincare.matf.bg.ac.rs/~ezivkovm/publications/primpol1.pdf + // (the shift values are the polynomial values minus one + // due to counting bits from 0 to 63). As the current + // position is always the LSB, the polynomial only needs + // to shift data in from the left without wrap. + data ^= tmp; + data ^= (data >> 63) & 1; + data ^= (data >> 60) & 1; + data ^= (data >> 55) & 1; + data ^= (data >> 30) & 1; + data ^= (data >> 27) & 1; + data ^= (data >> 22) & 1; + data = data.rotate_left(1); + } + data + } + + // Note: in the reference implementation only the last round effects + // `self.data`, all the other results are ignored. To make sure the + // other rounds are not optimised out, we first run all but the last + // round on a throw-away value instead of the real `self.data`. + let mut lfsr_loop_cnt = 0; + if var_rounds { lfsr_loop_cnt = self.random_loop_cnt(4) }; + + let mut throw_away: u64 = 0; + for _ in 0..lfsr_loop_cnt { + throw_away = lfsr(throw_away, time); + } + black_box(throw_away); + + self.data = lfsr(self.data, time); + } + + // Memory Access noise source + // This is a noise source based on variations in memory access times + // + // This function performs memory accesses which will add to the timing + // variations due to an unknown amount of CPU wait states that need to be + // added when accessing memory. The memory size should be larger than the L1 + // caches as outlined in the documentation and the associated testing. + // + // The L1 cache has a very high bandwidth, albeit its access rate is usually + // slower than accessing CPU registers. Therefore, L1 accesses only add + // minimal variations as the CPU has hardly to wait. Starting with L2, + // significant variations are added because L2 typically does not belong to + // the CPU any more and therefore a wider range of CPU wait states is + // necessary for accesses. L3 and real memory accesses have even a wider + // range of wait states. However, to reliably access either L3 or memory, + // the `self.mem` memory must be quite large which is usually not desirable. + #[inline(never)] + fn memaccess(&mut self, var_rounds: bool) { + let mut acc_loop_cnt = 128; + if var_rounds { acc_loop_cnt += self.random_loop_cnt(4) }; + + let mut index = self.mem_prev_index; + for _ in 0..acc_loop_cnt { + // Addition of memblocksize - 1 to index with wrap around logic to + // ensure that every memory location is hit evenly. + // The modulus also allows the compiler to remove the indexing + // bounds check. + index = (index + MEMORY_BLOCKSIZE - 1) % MEMORY_SIZE; + + // memory access: just add 1 to one byte + // memory access implies read from and write to memory location + let tmp = self.mem[index]; + self.mem[index] = tmp.wrapping_add(1); + } + self.mem_prev_index = index; + } + + + // Stuck test by checking the: + // - 1st derivation of the jitter measurement (time delta) + // - 2nd derivation of the jitter measurement (delta of time deltas) + // - 3rd derivation of the jitter measurement (delta of delta of time + // deltas) + // + // All values must always be non-zero. + // This test is a heuristic to see whether the last measurement holds + // entropy. + fn stuck(&mut self, current_delta: i64) -> bool { + let delta2 = self.last_delta - current_delta; + let delta3 = delta2 - self.last_delta2; + + self.last_delta = current_delta; + self.last_delta2 = delta2; + + current_delta == 0 || delta2 == 0 || delta3 == 0 + } + + // This is the heart of the entropy generation: calculate time deltas and + // use the CPU jitter in the time deltas. The jitter is injected into the + // entropy pool. + // + // Ensure that `self.prev_time` is primed before using the output of this + // function. This can be done by calling this function and not using its + // result. + fn measure_jitter(&mut self) -> Option<()> { + // Invoke one noise source before time measurement to add variations + self.memaccess(true); + + // Get time stamp and calculate time delta to previous + // invocation to measure the timing variations + let time = (self.timer)(); + // Note: wrapping_sub combined with a cast to `i64` generates a correct + // delta, even in the unlikely case this is a timer that is not strictly + // monotonic. + let current_delta = time.wrapping_sub(self.prev_time) as i64; + self.prev_time = time; + + // Call the next noise source which also injects the data + self.lfsr_time(current_delta as u64, true); + + // Check whether we have a stuck measurement (i.e. does the last + // measurement holds entropy?). + if self.stuck(current_delta) { return None }; + + // Rotate the data buffer by a prime number (any odd number would + // do) to ensure that every bit position of the input time stamp + // has an even chance of being merged with a bit position in the + // entropy pool. We do not use one here as the adjacent bits in + // successive time deltas may have some form of dependency. The + // chosen value of 7 implies that the low 7 bits of the next + // time delta value is concatenated with the current time delta. + self.data = self.data.rotate_left(7); + + Some(()) + } + + // Shuffle the pool a bit by mixing some value with a bijective function + // (XOR) into the pool. + // + // The function generates a mixer value that depends on the bits set and + // the location of the set bits in the random number generated by the + // entropy source. Therefore, based on the generated random number, this + // mixer value can have 2^64 different values. That mixer value is + // initialized with the first two SHA-1 constants. After obtaining the + // mixer value, it is XORed into the random number. + // + // The mixer value is not assumed to contain any entropy. But due to the + // XOR operation, it can also not destroy any entropy present in the + // entropy pool. + #[inline(never)] + fn stir_pool(&mut self) { + // This constant is derived from the first two 32 bit initialization + // vectors of SHA-1 as defined in FIPS 180-4 section 5.3.1 + // The order does not really matter as we do not rely on the specific + // numbers. We just pick the SHA-1 constants as they have a good mix of + // bit set and unset. + const CONSTANT: u64 = 0x67452301efcdab89; + + // The start value of the mixer variable is derived from the third + // and fourth 32 bit initialization vector of SHA-1 as defined in + // FIPS 180-4 section 5.3.1 + let mut mixer = 0x98badcfe10325476; + + // This is a constant time function to prevent leaking timing + // information about the random number. + // The normal code is: + // ``` + // for i in 0..64 { + // if ((self.data >> i) & 1) == 1 { mixer ^= CONSTANT; } + // } + // ``` + // This is a bit fragile, as LLVM really wants to use branches here, and + // we rely on it to not recognise the opportunity. + for i in 0..64 { + let apply = (self.data >> i) & 1; + let mask = !apply.wrapping_sub(1); + mixer ^= CONSTANT & mask; + mixer = mixer.rotate_left(1); + } + + self.data ^= mixer; + } + + fn gen_entropy(&mut self) -> u64 { + // Prime `self.prev_time`, and run the noice sources to make sure the + // first loop round collects the expected entropy. + let _ = self.measure_jitter(); + + for _ in 0..self.rounds { + // If a stuck measurement is received, repeat measurement + // Note: we do not guard against an infinite loop, that would mean + // the timer suddenly became broken. + while self.measure_jitter().is_none() {} + } + + self.stir_pool(); + self.data + } + + /// Basic quality tests on the timer, by measuring CPU timing jitter a few + /// hundred times. + /// + /// If succesful, this will return the estimated number of rounds necessary + /// to collect 64 bits of entropy. Otherwise a `TimerError` with the cause + /// of the failure will be returned. + pub fn test_timer(&mut self) -> Result<u32, TimerError> { + // We could add a check for system capabilities such as `clock_getres` + // or check for `CONFIG_X86_TSC`, but it does not make much sense as the + // following sanity checks verify that we have a high-resolution timer. + + #[cfg(all(target_arch = "wasm32", not(target_os = "emscripten")))] + return Err(TimerError::NoTimer); + + let mut delta_sum = 0; + let mut old_delta = 0; + + let mut time_backwards = 0; + let mut count_mod = 0; + let mut count_stuck = 0; + + // TESTLOOPCOUNT needs some loops to identify edge systems. + // 100 is definitely too little. + const TESTLOOPCOUNT: u64 = 300; + const CLEARCACHE: u64 = 100; + + for i in 0..(CLEARCACHE + TESTLOOPCOUNT) { + // Measure time delta of core entropy collection logic + let time = (self.timer)(); + self.memaccess(true); + self.lfsr_time(time, true); + let time2 = (self.timer)(); + + // Test whether timer works + if time == 0 || time2 == 0 { + return Err(TimerError::NoTimer); + } + let delta = time2.wrapping_sub(time) as i64; + + // Test whether timer is fine grained enough to provide delta even + // when called shortly after each other -- this implies that we also + // have a high resolution timer + if delta == 0 { + return Err(TimerError::CoarseTimer); + } + + // Up to here we did not modify any variable that will be + // evaluated later, but we already performed some work. Thus we + // already have had an impact on the caches, branch prediction, + // etc. with the goal to clear it to get the worst case + // measurements. + if i < CLEARCACHE { continue; } + + if self.stuck(delta) { count_stuck += 1; } + + // Test whether we have an increasing timer. + if !(time2 > time) { time_backwards += 1; } + + // Count the number of times the counter increases in steps of 100ns + // or greater. + if (delta % 100) == 0 { count_mod += 1; } + + // Ensure that we have a varying delta timer which is necessary for + // the calculation of entropy -- perform this check only after the + // first loop is executed as we need to prime the old_delta value + delta_sum += (delta - old_delta).abs() as u64; + old_delta = delta; + } + + // We allow the time to run backwards for up to three times. + // This can happen if the clock is being adjusted by NTP operations. + // If such an operation just happens to interfere with our test, it + // should not fail. The value of 3 should cover the NTP case being + // performed during our test run. + if time_backwards > 3 { + return Err(TimerError::NotMonotonic); + } + + // Test that the available amount of entropy per round does not get to + // low. We expect 1 bit of entropy per round as a reasonable minimum + // (although less is possible, it means the collector loop has to run + // much more often). + // `assert!(delta_average >= log2(1))` + // `assert!(delta_sum / TESTLOOPCOUNT >= 1)` + // `assert!(delta_sum >= TESTLOOPCOUNT)` + if delta_sum < TESTLOOPCOUNT { + return Err(TimerError::TinyVariantions); + } + + // Ensure that we have variations in the time stamp below 100 for at + // least 10% of all checks -- on some platforms, the counter increments + // in multiples of 100, but not always + if count_mod > (TESTLOOPCOUNT * 9 / 10) { + return Err(TimerError::CoarseTimer); + } + + // If we have more than 90% stuck results, then this Jitter RNG is + // likely to not work well. + if count_stuck > (TESTLOOPCOUNT * 9 / 10) { + return Err(TimerError::TooManyStuck); + } + + // Estimate the number of `measure_jitter` rounds necessary for 64 bits + // of entropy. + // + // We don't try very hard to come up with a good estimate of the + // available bits of entropy per round here for two reasons: + // 1. Simple estimates of the available bits (like Shannon entropy) are + // too optimistic. + // 2) Unless we want to waste a lot of time during intialization, there + // only a small number of samples are available. + // + // Therefore we use a very simple and conservative estimate: + // `let bits_of_entropy = log2(delta_average) / 2`. + // + // The number of rounds `measure_jitter` should run to collect 64 bits + // of entropy is `64 / bits_of_entropy`. + // + // To have smaller rounding errors, intermediate values are multiplied + // by `FACTOR`. To compensate for `log2` and division rounding down, + // add 1. + let delta_average = delta_sum / TESTLOOPCOUNT; + // println!("delta_average: {}", delta_average); + + const FACTOR: u32 = 3; + fn log2(x: u64) -> u32 { 64 - x.leading_zeros() } + + // pow(δ, FACTOR) must be representable; if you have overflow reduce FACTOR + Ok(64 * 2 * FACTOR / (log2(delta_average.pow(FACTOR)) + 1)) + } + + /// Statistical test: return the timer delta of one normal run of the + /// `JitterEntropy` entropy collector. + /// + /// Setting `var_rounds` to `true` will execute the memory access and the + /// CPU jitter noice sources a variable amount of times (just like a real + /// `JitterEntropy` round). + /// + /// Setting `var_rounds` to `false` will execute the noice sources the + /// minimal number of times. This can be used to measure the minimum amount + /// of entropy one round of entropy collector can collect in the worst case. + /// + /// # Example + /// + /// Use `timer_stats` to run the [NIST SP 800-90B Entropy Estimation Suite] + /// (https://github.com/usnistgov/SP800-90B_EntropyAssessment). + /// + /// This is the recommended way to test the quality of `JitterRng`. It + /// should be run before using the RNG on untested hardware, after changes + /// that could effect how the code is optimised, and after major compiler + /// compiler changes, like a new LLVM version. + /// + /// First generate two files `jitter_rng_var.bin` and `jitter_rng_var.min`. + /// + /// Execute `python noniid_main.py -v jitter_rng_var.bin 8`, and validate it + /// with `restart.py -v jitter_rng_var.bin 8 <min-entropy>`. + /// This number is the expected amount of entropy that is at least available + /// for each round of the entropy collector. This number should be greater + /// than the amount estimated with `64 / test_timer()`. + /// + /// Execute `python noniid_main.py -v -u 4 jitter_rng_var.bin 4`, and + /// validate it with `restart.py -v -u 4 jitter_rng_var.bin 4 <min-entropy>`. + /// This number is the expected amount of entropy that is available in the + /// last 4 bits of the timer delta after running noice sources. Note that + /// a value of 3.70 is the minimum estimated entropy for true randomness. + /// + /// Execute `python noniid_main.py -v -u 4 jitter_rng_var.bin 4`, and + /// validate it with `restart.py -v -u 4 jitter_rng_var.bin 4 <min-entropy>`. + /// This number is the expected amount of entropy that is available to the + /// entropy collecter if both noice sources only run their minimal number of + /// times. This measures the absolute worst-case, and gives a lower bound + /// for the available entropy. + /// + /// ```rust,no_run + /// use rand::JitterRng; + /// + /// # use std::error::Error; + /// # use std::fs::File; + /// # use std::io::Write; + /// # + /// # fn try_main() -> Result<(), Box<Error>> { + /// fn get_nstime() -> u64 { + /// use std::time::{SystemTime, UNIX_EPOCH}; + /// + /// let dur = SystemTime::now().duration_since(UNIX_EPOCH).unwrap(); + /// // The correct way to calculate the current time is + /// // `dur.as_secs() * 1_000_000_000 + dur.subsec_nanos() as u64` + /// // But this is faster, and the difference in terms of entropy is + /// // negligible (log2(10^9) == 29.9). + /// dur.as_secs() << 30 | dur.subsec_nanos() as u64 + /// } + /// + /// // Do not initialize with `JitterRng::new`, but with `new_with_timer`. + /// // 'new' always runst `test_timer`, and can therefore fail to + /// // initialize. We want to be able to get the statistics even when the + /// // timer test fails. + /// let mut rng = JitterRng::new_with_timer(get_nstime); + /// + /// // 1_000_000 results are required for the NIST SP 800-90B Entropy + /// // Estimation Suite + /// // FIXME: this number is smaller here, otherwise the Doc-test is too slow + /// const ROUNDS: usize = 10_000; + /// let mut deltas_variable: Vec<u8> = Vec::with_capacity(ROUNDS); + /// let mut deltas_minimal: Vec<u8> = Vec::with_capacity(ROUNDS); + /// + /// for _ in 0..ROUNDS { + /// deltas_variable.push(rng.timer_stats(true) as u8); + /// deltas_minimal.push(rng.timer_stats(false) as u8); + /// } + /// + /// // Write out after the statistics collection loop, to not disturb the + /// // test results. + /// File::create("jitter_rng_var.bin")?.write(&deltas_variable)?; + /// File::create("jitter_rng_min.bin")?.write(&deltas_minimal)?; + /// # + /// # Ok(()) + /// # } + /// # + /// # fn main() { + /// # try_main().unwrap(); + /// # } + /// ``` + #[cfg(feature="std")] + pub fn timer_stats(&mut self, var_rounds: bool) -> i64 { + let time = platform::get_nstime(); + self.memaccess(var_rounds); + self.lfsr_time(time, var_rounds); + let time2 = platform::get_nstime(); + time2.wrapping_sub(time) as i64 + } +} + +#[cfg(feature="std")] +mod platform { + #[cfg(not(any(target_os = "macos", target_os = "ios", target_os = "windows", all(target_arch = "wasm32", not(target_os = "emscripten")))))] + pub fn get_nstime() -> u64 { + use std::time::{SystemTime, UNIX_EPOCH}; + + let dur = SystemTime::now().duration_since(UNIX_EPOCH).unwrap(); + // The correct way to calculate the current time is + // `dur.as_secs() * 1_000_000_000 + dur.subsec_nanos() as u64` + // But this is faster, and the difference in terms of entropy is negligible + // (log2(10^9) == 29.9). + dur.as_secs() << 30 | dur.subsec_nanos() as u64 + } + + #[cfg(any(target_os = "macos", target_os = "ios"))] + pub fn get_nstime() -> u64 { + extern crate libc; + // On Mac OS and iOS std::time::SystemTime only has 1000ns resolution. + // We use `mach_absolute_time` instead. This provides a CPU dependent unit, + // to get real nanoseconds the result should by multiplied by numer/denom + // from `mach_timebase_info`. + // But we are not interested in the exact nanoseconds, just entropy. So we + // use the raw result. + unsafe { libc::mach_absolute_time() } + } + + #[cfg(target_os = "windows")] + pub fn get_nstime() -> u64 { + extern crate winapi; + unsafe { + let mut t = super::mem::zeroed(); + winapi::um::profileapi::QueryPerformanceCounter(&mut t); + *t.QuadPart() as u64 + } + } + + #[cfg(all(target_arch = "wasm32", not(target_os = "emscripten")))] + pub fn get_nstime() -> u64 { + unreachable!() + } +} + +// A function that is opaque to the optimizer to assist in avoiding dead-code +// elimination. Taken from `bencher`. +fn black_box<T>(dummy: T) -> T { + unsafe { + let ret = ptr::read_volatile(&dummy); + mem::forget(dummy); + ret + } +} + +impl Rng for JitterRng { + fn next_u32(&mut self) -> u32 { + // We want to use both parts of the generated entropy + if let Some(high) = self.data_remaining.take() { + high + } else { + let data = self.next_u64(); + self.data_remaining = Some((data >> 32) as u32); + data as u32 + } + } + + fn next_u64(&mut self) -> u64 { + self.gen_entropy() + } + + fn fill_bytes(&mut self, dest: &mut [u8]) { + let mut left = dest; + while left.len() >= 8 { + let (l, r) = {left}.split_at_mut(8); + left = r; + let chunk: [u8; 8] = unsafe { + mem::transmute(self.next_u64().to_le()) + }; + l.copy_from_slice(&chunk); + } + let n = left.len(); + if n > 0 { + let chunk: [u8; 8] = unsafe { + mem::transmute(self.next_u64().to_le()) + }; + left.copy_from_slice(&chunk[..n]); + } + } +} + +// There are no tests included because (1) this is an "external" RNG, so output +// is not reproducible and (2) `test_timer` *will* fail on some platforms. |