The lack of entropy available for, or used by, a Pseudo-Random Number Generator (PRNG) can be a stability and security threat.
Time of Introduction
Architecture and Design
Implementation
Applicable Platforms
Languages
All
Common Consequences
Scope
Effect
Availability
Technical Impact: DoS: crash / exit /
restart
If a pseudo-random number generator is using a limited entropy source
which runs out (if the generator fails closed), the program may pause or
crash.
Access Control
Other
Technical Impact: Bypass protection
mechanism; Other
If a PRNG is using a limited entropy source which runs out, and the
generator fails open, the generator could produce predictable random
numbers. Potentially a weak source of random numbers could weaken the
encryption method used for authentication of users.
Likelihood of Exploit
Medium
Potential Mitigations
Phases: Architecture and Design; Requirements
Strategy: Libraries or Frameworks
Use products or modules that conform to FIPS 140-2 [R.332.1] to avoid obvious entropy problems. Consult FIPS 140-2 Annex C ("Approved Random Number Generators").
Phase: Implementation
Consider a PRNG that re-seeds itself as needed from high-quality
pseudo-random output, such as hardware devices.
Phase: Architecture and Design
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.
Description
