CWE-338

Base 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
Use of Cryptographically Weak Pseudo-Random Number Generator (PRNG)

Description

The product uses a Pseudo-Random Number Generator (PRNG) in a security context, but the PRNG's algorithm is not cryptographically strong.

When a non-cryptographic PRNG is used in a cryptographic context, it can expose the cryptography to certain types of attacks. Often a pseudo-random number generator (PRNG) is not designed for cryptography. Sometimes a mediocre source of randomness is sufficient or preferable for algorithms that use random numbers. Weak generators generally take less processing power and/or do not use the precious, finite, entropy sources on a system. While such PRNGs might have very useful features, these same features could be used to break the cryptography.

Top Monitored CVEs

CVE-2021-43799
CRITICAL
9.8 5.4%
2022-01-25

Consequences

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.

Mitigations

Phase: 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.)