Weakness · High
CWE-338: Use of Cryptographically Weak Pseudo-Random Number Generator (PRNG)
What it is
The product uses a Pseudo-Random Number Generator (PRNG) in a security context, but the PRNG's algorithm is not cryptographically strong.
- Severity (our rating)
- High
- Likelihood of exploit
- Medium
- Introduced during
- Architecture and Design, Implementation
- Exploited in the wild
- No CVE in CISA's catalog
In more detail
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.
What an attacker can do
- Bypass Protection Mechanism (Access Control)
How to prevent it
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.
How to find it
- 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.)
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Start freeSource: MITRE Common Weakness Enumeration, CWE version 4.19.1. CWE is a trademark of The MITRE Corporation.