CWE-337: Predictable Seed in Pseudo-Random Number… | Glexia
CWE-337 (Predictable Seed in Pseudo-Random Number Generator (PRNG)) weakness overview with consequences, detection methods, mitigations, related CVEs and MITRE…
Glexia's Take · Automated analysis
CWE-337: Predictable Seed in Pseudo-Random Number Generator (PRNG)
Predictable Seed in Pseudo-Random Number Generator (PRNG) represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.
Executive Impact
- Other: Varies by Context
Developer Pattern
CWE-337 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-337, 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-337: Predictable Seed in Pseudo-Random Number Generator (PRNG)
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.
Developer And Remediation Guidance
How teams prevent and detect this weakness
Causes
- Both of these examples use a statistical PRNG seeded with the current value of the system clock to generate a random number: An attacker can easily predict the seed used by these PRNGs, and so also predict the stream of random numbers generated. Note these examples also exhibit CWE-338 (Use of Cryptographically Weak PRNG).
Remediation
- Use non-predictable inputs for seed generation.
- 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.
- 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.)
Mappings
Related CVEs, CWEs, and ATT&CK context
ATT&CK Relevance
ATT&CK relevance is shown only when reviewed or responsibly inferred.