CWE-337

Predictable Seed in Pseudo-Random Number Generator (PRNG)
AI Translation Available

A Pseudo-Random Number Generator (PRNG) is initialized from a predictable seed, such as the process ID or system time.

Status
draft
Abstraction
variant

The use of predictable seeds significantly reduces the number of possible seeds that an attacker would need to test in order to predict which random numbers will be generated by the PRNG.

Common Consequences

other
Impacts
varies by context

Detection Methods

automated static analysis

Potential Mitigations

Phases:
architecture and design requirements implementation
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 non-predictable inputs for seed generation.
• Use a PRNG that periodically re-seeds itself using input from high-quality sources, such as hardware devices with high entropy. However, do not re-seed too frequently, or else the entropy source might block.