CWE-332

Variant Abstraction Level
Pillar — Highest-level weakness category
Class — Abstract, language-independent
Base — Specific enough to detect
Variant — Tied to specific technology
Compound — Requires multiple weaknesses Draft MITRE CWE Status
Stable — Fully reviewed and complete
Draft — Under development, may change
Incomplete — Partially defined by MITRE
Deprecated — No longer recommended
Obsolete — Replaced by another CWE Exploit: Medium
Insufficient Entropy in PRNG

Description

The lack of entropy available for, or used by, a Pseudo-Random Number Generator (PRNG) can be a stability and security threat.

Consequences

Availability — DoS: Crash, Exit, or 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 — 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.

Mitigations

Phase: Architecture and Design, Requirements

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").

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.

Detection

Automated Static Analysis

Automated static analysis, commonly referred to as Static Application Security Testing (SAST), can find some instances of this weakness by analyzing source code (or binary/compiled code) without having to execute it. Typically, this is done by building a model of data flow and control flow, then searching for potentially-vulnerable patterns that connect "sources" (origins of input) with "sinks" (destinations where the data interacts with external components, a lower layer such as the OS, etc.)