Using pseudorandom number generators (PRNGs) is security-sensitive. For example, it has led in the past to the following vulnerabilities:
When software generates predictable values in a context requiring unpredictability, it may be possible for an attacker to guess the next value that
will be generated, and use this guess to impersonate another user or access sensitive information.
As the functions rely on a pseudorandom number generator, they should not be used for security-critical applications or for protecting sensitive
data.
Ask Yourself Whether
- the code using the generated value requires it to be unpredictable. It is the case for all encryption mechanisms or when a secret value, such
as a password, is hashed.
- the function you use generates a value which can be predicted (pseudo-random).
- the generated value is used multiple times.
- an attacker can access the generated value.
There is a risk if you answered yes to any of those questions.
Recommended Secure Coding Practices
- Use functions which rely on a strong random number generator such as
randombytes_uniform() or randombytes_buf() from
libsodium, or randomize() from Botan.
- Use the generated random values only once.
- You should not expose the generated random value. If you have to store it, make sure that the database or file is secure.
Sensitive Code Example
#include <random>
// ...
void f() {
int random_int = std::rand(); // Sensitive
}
Compliant Solution
#include <sodium.h>
#include <botan/system_rng.h>
// ...
void f() {
char random_chars[10];
randombytes_buf(random_chars, 10); // Compliant
uint32_t random_int = randombytes_uniform(10); // Compliant
uint8_t random_chars[10];
Botan::System_RNG system;
system.randomize(random_chars, 10); // Compliant
}
See
