random(4freebsd)
NAME
random --- the entropy device
SYNOPSIS
device random
options RANDOM_LOADABLE
options RANDOM_ENABLE_UMA
DESCRIPTION
The random device returns an endless supply of random bytes when read.
It also accepts and reads data as any ordinary file.
The generator will start in an unseeded state, and will block reads until
it is seeded for the first time. This may cause trouble at system boot
when keys and the like are generated from random so steps should be taken
to ensure a seeding as soon as possible.
It is also possible to read random bytes by using the KERN_ARND sysctl.
On the command line this could be done by
sysctl -x -B 16 kern.arandom
This sysctl will not return random bytes unless the random device is
seeded.
This initial seeding of random number generators is a bootstrapping
problem that needs very careful attention. In some cases, it may be
difficult to find enough randomness to seed a random number generator
until a system is fully operational, but the system requires random
numbers to become fully operational. It is (or more accurately should
be) critically important that the random device is seeded before the
first time it is used. In the case where a dummy or "blocking-only"
device is used, it is the responsibility of the system architect to
ensure that no blocking reads hold up critical processes.
To see the current settings of the software random device, use the
command line:
sysctl kern.random
which results in something like:
kern.random.fortuna.minpoolsize: 64
kern.random.harvest.mask_symbolic: [HIGH_PERFORMANCE], ... ,CACHED
kern.random.harvest.mask_bin: 00111111111
kern.random.harvest.mask: 511
kern.random.random_sources: 'Intel Secure Key RNG'
Other than
kern.random.fortuna.minpoolsize
and
kern.random.harvest.mask
all settings are read-only.
The kern.random.fortuna.minpoolsize sysctl is used to set the seed
threshold. A smaller number gives a faster seed, but a less secure one.
In practice, values between 64 and 256 are acceptable.
The kern.random.harvest.mask bitmask is used to select the possible
entropy sources. A 0 (zero) value means the corresponding source is not
considered as an entropy source. Set the bit to 1 (one) if you wish to
use that source. The kern.random.harvest.mask_bin and
kern.random.harvest.mask_symbolic sysctls can be used to confirm that the
choices are correct. Note that disabled items in the latter item are
listed in square brackets. See random_harvest(9) for more on the
harvesting of entropy.
When options RANDOM_LOADABLE is used, the /dev/random device is not
created until an "algorithm module" is loaded. Two of these modules are
built by default, random_fortuna and random_yarrow. The random_yarrow
module is deprecated, and will be removed in FreeBSD 12. Use of the
Yarrow algorithm is not encouraged, but while still present in the kernel
source, it can be selected with the options RANDOM_YARROW kernel option.
Note that these loadable modules are slightly less efficient than their
compiled-in equivalents. This is because some functions must be locked
against load and unload events, and also must be indirect calls to allow
for removal.
When options RANDOM_ENABLE_UMA is used, the /dev/random device will
obtain entropy from the zone allocator. This is potentially very high
rate, and if so will be of questionable use. If this is the case, use of
this option is not recommended. Determining this is not trivial, so
experimenting and measurement using tools such as dtrace(1) will be
required.
RANDOMNESS
The use of randomness in the field of computing is a rather subtle issue
because randomness means different things to different people. Consider
generating a password randomly, simulating a coin tossing experiment or
choosing a random back-off period when a server does not respond. Each
of these tasks requires random numbers, but the random numbers in each
case have different requirements.
Generation of passwords, session keys and the like requires cryptographic
randomness. A cryptographic random number generator should be designed
so that its output is difficult to guess, even if a lot of auxiliary
information is known (such as when it was seeded, subsequent or previous
output, and so on). On FreeBSD, seeding for cryptographic random number
generators is provided by the random device, which provides real
randomness. The arc4random(3) library call provides a pseudo-random
sequence which is generally reckoned to be suitable for simple
cryptographic use. The OpenSSL library also provides functions for
managing randomness via functions such as RAND_bytes(3) and RAND_add(3).
Note that OpenSSL uses the random device for seeding automatically.
Randomness for simulation is required in engineering or scientific
software and games. The first requirement of these applications is that
the random numbers produced conform to some well-known, usually uniform,
distribution. The sequence of numbers should also appear numerically
uncorrelated, as simulation often assumes independence of its random
inputs. Often it is desirable to reproduce the results of a simulation
exactly, so that if the generator is seeded in the same way, it should
produce the same results. A peripheral concern for simulation is the
speed of a random number generator.
Another issue in simulation is the size of the state associated with the
random number generator, and how frequently it repeats itself. For
example, a program which shuffles a pack of cards should have 52!
possible outputs, which requires the random number generator to have 52!
starting states. This means the seed should have at least log_2(52!) ~
226 bits of state if the program is to stand a chance of outputting all
possible sequences, and the program needs some unbiased way of generating
these bits. Again, the random device could be used for seeding here, but
in practice, smaller seeds are usually considered acceptable.
FreeBSD provides two families of functions which are considered suitable
for simulation. The random(3) family of functions provides a random
integer between 0 to (2**31)1. The functions srandom(3), initstate(3)
and setstate(3) are provided for deterministically setting the state of
the generator and the function srandomdev(3) is provided for setting the
state via the random device. The drand48(3) family of functions are also
provided, which provide random floating point numbers in various ranges.
Randomness that is used for collision avoidance (for example, in certain
network protocols) has slightly different semantics again. It is usually
expected that the numbers will be uniform, as this produces the lowest
chances of collision. Here again, the seeding of the generator is very
important, as it is required that different instances of the generator
produce independent sequences. However, the guessability or
reproducibility of the sequence is unimportant, unlike the previous
cases.
FreeBSD does also provide the traditional rand(3) library call, for
compatibility purposes. However, it is known to be poor for simulation
and absolutely unsuitable for cryptographic purposes, so its use is
discouraged.
FILES
/dev/random
SEE ALSO
arc4random(3), drand48(3), rand(3), RAND_add(3), RAND_bytes(3),
random(3), sysctl(8), random(9)
Ferguson, Schneier, and Kohno, Cryptography Engineering, Wiley, ISBN
978-0-470-47424-2.
HISTORY
A random device appeared in FreeBSD 2.2. The current software
implementation, introduced in FreeBSD 10.0, is by Mark R V Murray, and is
an implementation of the Fortuna algorithm by Ferguson et al. It
replaces the previous Yarrow implementation, introduced in FreeBSD 5.0.
The Yarrow algorithm is no longer supported by its authors, and is
therefore deprecated.
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