💾 Archived View for gmi.noulin.net › man › man7 › random.7.gmi captured on 2023-12-28 at 17:41:11. Gemini links have been rewritten to link to archived content
⬅️ Previous capture (2022-06-12)
-=-=-=-=-=-=-
RANDOM(7) Linux Programmer's Manual RANDOM(7)
NAME
random - overview of interfaces for obtaining randomness
DESCRIPTION
The kernel random-number generator relies on entropy gathered from device drivers and other sources of environmental noise to seed a cryptographically secure
pseudorandom number generator (CSPRNG). It is designed for security, rather than speed.
The following interfaces provide access to output from the kernel CSPRNG:
* The /dev/urandom and /dev/random devices, both described in random(4). These devices have been present on Linux since early times, and are also available on
many other systems.
* The Linux-specific getrandom(2) system call, available since Linux 3.17. This system call provides access either to the same source as /dev/urandom (called
the urandom source in this page) or to the same source as /dev/random (called the random source in this page). The default is the urandom source; the random
source is selected by specifying the GRND_RANDOM flag to the system call. (The getentropy(3) function provides a slightly more portable interface on top of
getrandom(2).)
Initialization of the entropy pool
The kernel collects bits of entropy from the environment. When a sufficient number of random bits has been collected, the entropy pool is considered to be ini‐
tialized.
Choice of random source
Unless you are doing long-term key generation (and most likely not even then), you probably shouldn't be reading from the /dev/random device or employing getran‐
dom(2) with the GRND_RANDOM flag. Instead, either read from the /dev/urandom device or employ getrandom(2) without the GRND_RANDOM flag. The cryptographic al‐
gorithms used for the urandom source are quite conservative, and so should be sufficient for all purposes.
The disadvantage of GRND_RANDOM and reads from /dev/random is that the operation can block for an indefinite period of time. Furthermore, dealing with the par‐
tially fulfilled requests that can occur when using GRND_RANDOM or when reading from /dev/random increases code complexity.
Monte Carlo and other probabilistic sampling applications
Using these interfaces to provide large quantities of data for Monte Carlo simulations or other programs/algorithms which are doing probabilistic sampling will
be slow. Furthermore, it is unnecessary, because such applications do not need cryptographically secure random numbers. Instead, use the interfaces described
in this page to obtain a small amount of data to seed a user-space pseudorandom number generator for use by such applications.
Comparison between getrandom, /dev/urandom, and /dev/random
The following table summarizes the behavior of the various interfaces that can be used to obtain randomness. GRND_NONBLOCK is a flag that can be used to control
the blocking behavior of getrandom(2). The final column of the table considers the case that can occur in early boot time when the entropy pool is not yet ini‐
tialized.
┌──────────────┬──────────────┬────────────────┬────────────────────┐
│Interface │ Pool │ Blocking │ Behavior when pool │
│ │ │ behavior │ is not yet ready │
├──────────────┼──────────────┼────────────────┼────────────────────┤
│/dev/random │ Blocking │ If entropy too │ Blocks until │
│ │ pool │ low, blocks │ enough entropy │
│ │ │ until there is │ gathered │
│ │ │ enough entropy │ │
│ │ │ again │ │
├──────────────┼──────────────┼────────────────┼────────────────────┤
│/dev/urandom │ CSPRNG out‐ │ Never blocks │ Returns output │
│ │ put │ │ from uninitialized │
│ │ │ │ CSPRNG (may be low │
│ │ │ │ entropy and un‐ │
│ │ │ │ suitable for cryp‐ │
│ │ │ │ tography) │
├──────────────┼──────────────┼────────────────┼────────────────────┤
│getrandom() │ Same as │ Does not block │ Blocks until pool │
│ │ /dev/urandom │ once is pool │ ready │
│ │ │ ready │ │
├──────────────┼──────────────┼────────────────┼────────────────────┤
│getrandom() │ Same as │ If entropy too │ Blocks until pool │
│GRND_RANDOM │ /dev/random │ low, blocks │ ready │
│ │ │ until there is │ │
│ │ │ enough entropy │ │
│ │ │ again │ │
├──────────────┼──────────────┼────────────────┼────────────────────┤
│getrandom() │ Same as │ Does not block │ EAGAIN │
│GRND_NONBLOCK │ /dev/urandom │ once is pool │ │
│ │ │ ready │ │
├──────────────┼──────────────┼────────────────┼────────────────────┤
│getrandom() │ Same as │ EAGAIN if not │ EAGAIN │
│GRND_RANDOM + │ /dev/random │ enough entropy │ │
│GRND_NONBLOCK │ │ available │ │
└──────────────┴──────────────┴────────────────┴────────────────────┘
Generating cryptographic keys
The amount of seed material required to generate a cryptographic key equals the effective key size of the key. For example, a 3072-bit RSA or Diffie-Hellman
private key has an effective key size of 128 bits (it requires about 2^128 operations to break) so a key generator needs only 128 bits (16 bytes) of seed mate‐
rial from /dev/random.
While some safety margin above that minimum is reasonable, as a guard against flaws in the CSPRNG algorithm, no cryptographic primitive available today can hope
to promise more than 256 bits of security, so if any program reads more than 256 bits (32 bytes) from the kernel random pool per invocation, or per reasonable
reseed interval (not less than one minute), that should be taken as a sign that its cryptography is not skillfully implemented.
SEE ALSO
getrandom(2), getauxval(3), getentropy(3), random(4), urandom(4), signal(7)
Linux 2017-03-13 RANDOM(7)