CWE-337

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
Predictable Seed in Pseudo-Random Number Generator (PRNG)

Description

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

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.

Consequences

Other — Varies by Context

Mitigations

Phase:

Use non-predictable inputs for seed generation.

Phase: Architecture and Design, Requirements

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.

Phase: Implementation

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.

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.)