Add nitrokey as a dependency to nitrocli

The nitrokey crate provides a simple interface to the Nitrokey Storage
and the Nitrokey Pro based on the libnitrokey library developed by
Nitrokey UG.  The low-level bindings to this library are available in
the nitrokey-sys crate.

This patch adds version v0.2.1 of the nitrokey crate as a dependency
for nitrocli.  It includes the indirect dependencies nitrokey-sys
(version 3.4.1) and rand (version 0.4.3).

Import subrepo nitrokey/:nitrokey at 2eccc96ceec2282b868891befe9cda7f941fbe7b
Import subrepo nitrokey-sys/:nitrokey-sys at f1a11ebf72610fb9cf80ac7f9f147b4ba1a5336f
Import subrepo rand/:rand at d7d5da49daf7ceb3e5940072940d495cced3a1b3

1 files changed, 754 insertions, 0 deletions

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.