CWE-332
Insufficient Entropy in PRNG
AI Translation Available
The lack of entropy available for, or used by, a Pseudo-Random Number Generator (PRNG) can be a stability and security threat.
Status
draft
Abstraction
variant
Likelihood
medium
Affected Platforms
Technical Details
AI Translation
Common Consequences
availability
access control
other
Impacts
dos: crash, exit, or restart
bypass protection mechanism
other
Detection Methods
automated static analysis
Potential Mitigations
Phases:
architecture and design
requirements
implementation
Descriptions:
•
Consider a PRNG that re-seeds itself as needed from high-quality pseudo-random output, such as hardware devices.
•
Use products or modules that conform to FIPS 140-2 [REF-267] to avoid obvious entropy problems. Consult FIPS 140-2 Annex C ("Approved Random Number Generators").
•
When deciding which PRNG to use, look at its sources of entropy. Depending on what your security needs are, you may need to use a random number generator that always uses strong random data -- i.e., a random number generator that attempts to be strong but will fail in a weak way or will always provide some middle ground of protection through techniques like re-seeding. Generally, something that always provides a predictable amount of strength is preferable.