rand - pseudo-random number generator
int RAND_set_rand_engine(ENGINE *engine);
int RAND_bytes(unsigned char *buf, int num);
int RAND_pseudo_bytes(unsigned char *buf, int num);
void RAND_seed(const void *buf, int num);
void RAND_add(const void *buf, int num, double entropy);
int RAND_load_file(const char *file, long max_bytes);
int RAND_write_file(const char *file);
const char *RAND_file_name(char *file, size_t num);
int RAND_egd(const char *path);
void RAND_set_rand_method(const RAND_METHOD *meth);
const RAND_METHOD *RAND_get_rand_method(void);
/* For Win32 only */
int RAND_event(UINT, WPARAM, LPARAM);
Since the introduction of the ENGINE API, the recommended way of con-
trolling default implementations is by using the ENGINE API functions.
The default RAND_METHOD, as set by RAND_set_rand_method() and returned
by RAND_get_rand_method(), is only used if no ENGINE has been set as
the default "rand" implementation. Hence, these two functions are no
longer the recommended way to control defaults.
If an alternative RAND_METHOD implementation is being used (either set
directly or as provided by an ENGINE module), then it is entirely
responsible for the generation and management of a cryptographically
secure PRNG stream. The mechanisms described below relate solely to the
software PRNG implementation built in to OpenSSL and used by default.
These functions implement a cryptographically secure pseudo-random num-
ber generator (PRNG). It is used by other library functions for example
to generate random keys, and applications can use it when they need
A cryptographic PRNG must be seeded with unpredictable data such as
mouse movements or keys pressed at random by the user. This is
described in RAND_add(3). Its state can be saved in a seed file (see
RAND_load_file(3)) to avoid having to go through the seeding process
whenever the application is started.
RAND_bytes(3) describes how to obtain random data from the PRNG.
The RAND_SSLeay() method implements a PRNG based on a cryptographic
The following description of its design is based on the SSLeay documen-
First up I will state the things I believe I need for a good RNG.
1 A good hashing algorithm to mix things up and to convert the RNG
'state' to random numbers.
2 An initial source of random 'state'.
3 The state should be very large. If the RNG is being used to gener-
ate 4096 bit RSA keys, 2 2048 bit random strings are required (at a
minimum). If your RNG state only has 128 bits, you are obviously
limiting the search space to 128 bits, not 2048. I'm probably get-
ting a little carried away on this last point but it does indicate
that it may not be a bad idea to keep quite a lot of RNG state. It
should be easier to break a cipher than guess the RNG seed data.
4 Any RNG seed data should influence all subsequent random numbers
generated. This implies that any random seed data entered will
have an influence on all subsequent random numbers generated.
5 When using data to seed the RNG state, the data used should not be
extractable from the RNG state. I believe this should be a
requirement because one possible source of 'secret' semi random
data would be a private key or a password. This data must not be
disclosed by either subsequent random numbers or a 'core' dump left
by a program crash.
6 Given the same initial 'state', 2 systems should deviate in their
RNG state (and hence the random numbers generated) over time if at
7 Given the random number output stream, it should not be possible to
determine the RNG state or the next random number.
The algorithm is as follows.
There is global state made up of a 1023 byte buffer (the 'state'), a
working hash value ('md'), and a counter ('count').
Whenever seed data is added, it is inserted into the 'state' as fol-
The input is chopped up into units of 20 bytes (or less for the last
block). Each of these blocks is run through the hash function as fol-
lows: The data passed to the hash function is the current 'md', the
same number of bytes from the 'state' (the location determined by in
incremented looping index) as the current 'block', the new key data
'block', and 'count' (which is incremented after each use). The result
of this is kept in 'md' and also xored into the 'state' at the same
locations that were used as input into the hash function. I believe
this system addresses points 1 (hash function; currently SHA-1), 3 (the
'state'), 4 (via the 'md'), 5 (by the use of a hash function and xor).
When bytes are extracted from the RNG, the following process is used.
For each group of 10 bytes (or less), we do the following:
Input into the hash function the local 'md' (which is initialized from
the global 'md' before any bytes are generated), the bytes that are to
be overwritten by the random bytes, and bytes from the 'state' (incre-
menting looping index). From this digest output (which is kept in
'md'), the top (up to) 10 bytes are returned to the caller and the bot-
tom 10 bytes are xored into the 'state'.
Finally, after we have finished 'num' random bytes for the caller,
'count' (which is incremented) and the local and global 'md' are fed
into the hash function and the results are kept in the global 'md'.
I believe the above addressed points 1 (use of SHA-1), 6 (by hashing
into the 'state' the 'old' data from the caller that is about to be
overwritten) and 7 (by not using the 10 bytes given to the caller to
update the 'state', but they are used to update 'md').
So of the points raised, only 2 is not addressed (but see RAND_add(3)).
BN_rand(3), RAND_add(3), RAND_load_file(3), RAND_egd(3), RAND_bytes(3),
1.0.2t 2019-09-10 rand(3)
Man(1) output converted with