GNU/Linux man pages

Livre :
Expressions régulières,
Syntaxe et mise en oeuvre :

ISBN : 978-2-7460-9712-4
EAN : 9782746097124
(Editions ENI)


CentOS 2.1AS







rand − pseudo-random number generator


 #include <openssl/rand.h>
 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, int entropy);
 int  RAND_status(void);
 void RAND_screen(void);
 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(RAND_METHOD *meth);
 RAND_METHOD *RAND_get_rand_method(void);
 void RAND_cleanup(void);


These functions implement a cryptographically secure pseudo-random number generator (PRNG). It is used by other library functions for example to generate random keys, and applications can use it when they need randomness.

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 hash function.

The following description of its design is based on the SSLeay documentation:

First up I will state the things I believe I need for a good RNG.


A good hashing algorithm to mix things up and to convert the RNG ’state’ to random numbers.


An initial source of random ’state’.


The state should be very large. If the RNG is being used to generate 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 getting 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.


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.


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.


Given the same initial ’state’, 2 systems should deviate in their RNG state (and hence the random numbers generated) over time if at all possible.


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 follows.

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 follows: 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’ (incrementing looping index). From this digest output (which is kept in ’md’), the top (up to) 10 bytes are returned to the caller and the bottom 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), RAND_set_rand_method(3), RAND_cleanup(3)