1 // Copyright 2018 Developers of the Rand project.
2 //
3 // Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
4 // https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
5 // <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
6 // option. This file may not be copied, modified, or distributed
7 // except according to those terms.
8 
9 //! Random number generators and adapters
10 //!
11 //! ## Background: Random number generators (RNGs)
12 //!
13 //! Computers cannot produce random numbers from nowhere. We classify
14 //! random number generators as follows:
15 //!
16 //! -   "True" random number generators (TRNGs) use hard-to-predict data sources
17 //!     (e.g. the high-resolution parts of event timings and sensor jitter) to
18 //!     harvest random bit-sequences, apply algorithms to remove bias and
19 //!     estimate available entropy, then combine these bits into a byte-sequence
20 //!     or an entropy pool. This job is usually done by the operating system or
21 //!     a hardware generator (HRNG).
22 //! -   "Pseudo"-random number generators (PRNGs) use algorithms to transform a
23 //!     seed into a sequence of pseudo-random numbers. These generators can be
24 //!     fast and produce well-distributed unpredictable random numbers (or not).
25 //!     They are usually deterministic: given algorithm and seed, the output
26 //!     sequence can be reproduced. They have finite period and eventually loop;
27 //!     with many algorithms this period is fixed and can be proven sufficiently
28 //!     long, while others are chaotic and the period depends on the seed.
29 //! -   "Cryptographically secure" pseudo-random number generators (CSPRNGs)
30 //!     are the sub-set of PRNGs which are secure. Security of the generator
31 //!     relies both on hiding the internal state and using a strong algorithm.
32 //!
33 //! ## Traits and functionality
34 //!
35 //! All RNGs implement the [`RngCore`] trait, as a consequence of which the
36 //! [`Rng`] extension trait is automatically implemented. Secure RNGs may
37 //! additionally implement the [`CryptoRng`] trait.
38 //!
39 //! All PRNGs require a seed to produce their random number sequence. The
40 //! [`SeedableRng`] trait provides three ways of constructing PRNGs:
41 //!
42 //! -   `from_seed` accepts a type specific to the PRNG
43 //! -   `from_rng` allows a PRNG to be seeded from any other RNG
44 //! -   `seed_from_u64` allows any PRNG to be seeded from a `u64` insecurely
45 //! -   `from_entropy` securely seeds a PRNG from fresh entropy
46 //!
47 //! Use the [`rand_core`] crate when implementing your own RNGs.
48 //!
49 //! ## Our generators
50 //!
51 //! This crate provides several random number generators:
52 //!
53 //! -   [`OsRng`] is an interface to the operating system's random number
54 //!     source. Typically the operating system uses a CSPRNG with entropy
55 //!     provided by a TRNG and some type of on-going re-seeding.
56 //! -   [`ThreadRng`], provided by the [`thread_rng`] function, is a handle to a
57 //!     thread-local CSPRNG with periodic seeding from [`OsRng`]. Because this
58 //!     is local, it is typically much faster than [`OsRng`]. It should be
59 //!     secure, though the paranoid may prefer [`OsRng`].
60 //! -   [`StdRng`] is a CSPRNG chosen for good performance and trust of security
61 //!     (based on reviews, maturity and usage). The current algorithm is ChaCha12,
62 //!     which is well established and rigorously analysed.
63 //!     [`StdRng`] provides the algorithm used by [`ThreadRng`] but without
64 //!     periodic reseeding.
65 //! -   [`SmallRng`] is an **insecure** PRNG designed to be fast, simple, require
66 //!     little memory, and have good output quality.
67 //!
68 //! The algorithms selected for [`StdRng`] and [`SmallRng`] may change in any
69 //! release and may be platform-dependent, therefore they should be considered
70 //! **not reproducible**.
71 //!
72 //! ## Additional generators
73 //!
74 //! **TRNGs**: The [`rdrand`] crate provides an interface to the RDRAND and
75 //! RDSEED instructions available in modern Intel and AMD CPUs.
76 //! The [`rand_jitter`] crate provides a user-space implementation of
77 //! entropy harvesting from CPU timer jitter, but is very slow and has
78 //! [security issues](https://github.com/rust-random/rand/issues/699).
79 //!
80 //! **PRNGs**: Several companion crates are available, providing individual or
81 //! families of PRNG algorithms. These provide the implementations behind
82 //! [`StdRng`] and [`SmallRng`] but can also be used directly, indeed *should*
83 //! be used directly when **reproducibility** matters.
84 //! Some suggestions are: [`rand_chacha`], [`rand_pcg`], [`rand_xoshiro`].
85 //! A full list can be found by searching for crates with the [`rng` tag].
86 //!
87 //! [`Rng`]: crate::Rng
88 //! [`RngCore`]: crate::RngCore
89 //! [`CryptoRng`]: crate::CryptoRng
90 //! [`SeedableRng`]: crate::SeedableRng
91 //! [`thread_rng`]: crate::thread_rng
92 //! [`rdrand`]: https://crates.io/crates/rdrand
93 //! [`rand_jitter`]: https://crates.io/crates/rand_jitter
94 //! [`rand_chacha`]: https://crates.io/crates/rand_chacha
95 //! [`rand_pcg`]: https://crates.io/crates/rand_pcg
96 //! [`rand_xoshiro`]: https://crates.io/crates/rand_xoshiro
97 //! [`rng` tag]: https://crates.io/keywords/rng
98 
99 #[cfg_attr(doc_cfg, doc(cfg(feature = "std")))]
100 #[cfg(feature = "std")] pub mod adapter;
101 
102 pub mod mock; // Public so we don't export `StepRng` directly, making it a bit
103               // more clear it is intended for testing.
104 
105 #[cfg(all(feature = "small_rng", target_pointer_width = "64"))]
106 mod xoshiro256plusplus;
107 #[cfg(all(feature = "small_rng", not(target_pointer_width = "64")))]
108 mod xoshiro128plusplus;
109 #[cfg(feature = "small_rng")] mod small;
110 
111 #[cfg(feature = "std_rng")] mod std;
112 #[cfg(all(feature = "std", feature = "std_rng"))] pub(crate) mod thread;
113 
114 #[cfg(feature = "small_rng")] pub use self::small::SmallRng;
115 #[cfg(feature = "std_rng")] pub use self::std::StdRng;
116 #[cfg(all(feature = "std", feature = "std_rng"))] pub use self::thread::ThreadRng;
117 
118 #[cfg_attr(doc_cfg, doc(cfg(feature = "getrandom")))]
119 #[cfg(feature = "getrandom")] pub use rand_core::OsRng;
120