CWE-332: Insufficient Entropy in PRNG | Glexia
CWE-332 (Insufficient Entropy in PRNG) weakness overview with consequences, detection methods, mitigations, related CVEs and MITRE ATT&CK context.
Glexia's Take · Automated analysis
CWE-332: Insufficient Entropy in PRNG
Insufficient Entropy in PRNG represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.
Executive Impact
- 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.
Developer Pattern
CWE-332 is the kind of defect developers can usually prevent with explicit validation, safer framework defaults, and tests that exercise hostile input or unsafe state transitions.
Automation confidence
high confidence from CWE-332, 4.20.
Generated from the cited source records. This long-tail analysis has not been individually reviewed by a named human.
Official CWE Definition
CWE-332: Insufficient Entropy in PRNG
The lack of entropy available for, or used by, a Pseudo-Random Number Generator (PRNG) can be a stability and security threat.
Developer And Remediation Guidance
How teams prevent and detect this weakness
Causes
- Missing validation
- Unsafe defaults
- Insufficient authorization or memory-safety invariant
Remediation
- 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").
- Implementation: Consider a PRNG that re-seeds itself as needed from high-quality pseudo-random output, such as hardware devices.
- 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.)
Mappings
Related CVEs, CWEs, and ATT&CK context
Related CWEs
ATT&CK Relevance
ATT&CK relevance is shown only when reviewed or responsibly inferred.