Pseudo random number generators use mathematical algorithms to produce a sequence of numbers with good statistical properties, but the numbers produced are not genuinely random.
The C Standard function rand (available in stdlib.h) does not have good random number properties. The numbers generated by rand have a comparatively short cycle, and the numbers may be predictable. To achieve the best random numbers possible, an implementation-specific function must be used.
The following code generates an ID with a numeric part produced by calling the rand() function. The IDs produced are predictable and have limited randomness.
enum {len = 12};
char id[len]; /* id will hold the ID, starting with the characters "ID" */
/* followed by a random integer */
int r;
int num;
/* ... */
r = rand(); /* generate a random integer */
num = snprintf(id, len, "ID%-d", r); /* generate the ID */
/* ... */
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A better pseudo random number generator is the BSD function random().
enum {len = 12};
char id[len]; /* id will hold the ID, starting with the characters "ID" */
/* followed by a random integer */
int r;
int num;
/* ... */
srandom(time(0)); /* seed the PRNG with the current time */
/* ... */
r = random(); /* generate a random integer */
num = snprintf(id, len, "ID%-d", r); /* generate the ID */
/* ... */
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However, the random() function uses time(0) as seed. With a trivial seed like time(0), however, the results from random() are also predictable.
When unpredictability really matters and speed is not an issue, use a true entropy source such as /dev/random or even a hardware source such as a quantum mirror. In most cases, however, it will be acceptable to simply use a pseudo-random number generator from a cryptographic library (such as a the Mersenne Twister) and seed it with data that are read from /dev/random.
The /dev/random device may block for a long time if there are not enough events going on to generate sufficient entropy.
A read from the
/dev/urandomdevice will not block waiting for more entropy. As a result, if there is not sufficient entropy in the entropy pool, the returned values are theoretically vulnerable to a cryptographic attack on the algorithms used by the driver. Knowledge of how to do this is not available in the current non-classified literature, but it is theoretically possible that such an attack may exist. If this is a concern in your application, use/dev/randominstead.
The rand48 family of functions provides another pseudo-random alternative.
long int li;
FILE* fd;
if(!(fd = fopen("/dev/random", "r")) {
/* Handle error condition */
}
if(fread(&li, sizeof(li), 1, fd) != sizeof(li)) {
/* Handle error condition */
}
fclose(fd);
printf("Random number: %ld\n", li);
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On Windows platforms, the CryptGenRandom() function may be used to generate cryptographically strong random numbers. It is important to note, however, that the exact details of the implementation are unknown, and it is undetermined as to what source of entropy the CryptGenRandom() uses.
If an application has access to a good random source, it can fill the
pbBufferbuffer with some random data before callingCryptGenRandom(). The CSP then uses this data to further randomize its internal seed. It is acceptable to omit the step of initializing thepbBufferbuffer before callingCryptGenRandom().
#include<Wincrypt.h>
HCRYPTPROV hCryptProv;
union {
BYTE bs[sizeof(long int)];
long int li;
} rand_buf;
if(!CryptGenRandom(hCryptProv, sizeof(rand_buf), &rand_buf) {
/* Handle error */
} else {
printf("Random number: %ld\n", rand_buf.li);
}
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Using the rand() function leads to possibly predictable random numbers.
Rule |
Severity |
Likelihood |
Remediation Cost |
Priority |
Level |
|---|---|---|---|---|---|
MSC30-C |
1 (low) |
1 (unlikely) |
1 (high) |
P1 |
L3 |
Search for vulnerabilities resulting from the violation of this rule on the CERT website.
\[[ISO/IEC 9899-1999|AA. C References#ISO/IEC 9899-1999]\] Section 7.20.2.1, "The rand function" |
MSC13-A. Detect and remove unused values 14. Miscellaneous (MSC) MSC31-C. Ensure that return values are compared against the proper type