CWE-338: Use of Cryptographically Weak Pseudo-Random… | Glexia
CWE-338 (Use of Cryptographically Weak Pseudo-Random Number Generator (PRNG)) weakness overview with consequences, detection methods, mitigations, related CVEs and…
Glexia's Take · Automated analysis
CWE-338: Use of Cryptographically Weak Pseudo-Random Number Generator (PRNG)
Use of Cryptographically Weak 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
- Access Control: Bypass Protection Mechanism: If a PRNG is used for authentication and authorization, such as a session ID or a seed for generating a cryptographic key, then an attacker may be able to easily guess the ID or cryptographic key and gain access to restricted functionality.
Developer Pattern
CWE-338 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-338, 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-338: Use of Cryptographically Weak Pseudo-Random Number Generator (PRNG)
The product uses a Pseudo-Random Number Generator (PRNG) in a security context, but the PRNG's algorithm is not cryptographically strong.
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: The random number functions used in these examples, rand() and Random.nextInt(), are not considered cryptographically strong. An attacker may be able to predict the random numbers generated by these functions. Note that these example also exhibit CWE-337 (Predictable Seed in PRNG).
Remediation
- Implementation: Use functions or hardware which use a hardware-based random number generation for all crypto. This is the recommended solution. Use CyptGenRandom on Windows, or hw_rand() on Linux.
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.