CWE-339

Small Seed Space in PRNG
AI Translation Available

A Pseudo-Random Number Generator (PRNG) uses a relatively small seed space, which makes it more susceptible to brute force attacks.

Status
draft
Abstraction
variant

PRNGs are entirely deterministic once seeded, so it should be extremely difficult to guess the seed. If an attacker can collect the outputs of a PRNG and then brute force the seed by trying every possibility to see which seed matches the observed output, then the attacker will know the output of any subsequent calls to the PRNG. A small seed space implies that the attacker will have far fewer possible values to try to exhaust all possibilities.

Common Consequences

other
Impacts
varies by context

Potential Mitigations

Phases:
architecture and design requirements
Descriptions:
• Use products or modules that conform to FIPS 140-2 [REF-267] to avoid obvious entropy problems, or use the more recent FIPS 140-3 [REF-1192] if possible.
• Use well vetted pseudo-random number generating algorithms with adequate length seeds. Pseudo-random number generators can produce predictable numbers if the generator is known and the seed can be guessed. A 256-bit seed is a good starting point for producing a "random enough" number.