CWE-338: 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.

Extended Description

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.

ThreatScore

Threat Mapped score: 1.8

Industry: Finiancial

Threat priority: P4 - Informational (Low)

Observed Examples (CVEs)

CVE: CVE-2021-3692

PHP framework uses mt_rand() function (Marsenne Twister) when generating tokens
CVE: CVE-2009-3278

Crypto product uses rand() library function to generate a recovery key, making it easier to conduct brute force attacks.
CVE: CVE-2009-3238

Random number generator can repeatedly generate the same value.
CVE: CVE-2009-2367

Web application generates predictable session IDs, allowing session hijacking.
CVE: CVE-2008-0166

SSL library uses a weak random number generator that only generates 65,536 unique keys.

Related Attack Patterns (CAPEC)

N/A

Attack TTPs

N/A

Modes of Introduction

Phase	Note
Architecture and Design	N/A
Implementation	REALIZATION: This weakness is caused during implementation of an architectural security tactic.

Common Consequences

Impact: Bypass Protection Mechanism — Notes: 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.

Potential Mitigations

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. (N/A)

Applicable Platforms

None (Not Language-Specific, Undetermined)

Demonstrative Examples

Intro: Both of these examples use a statistical PRNG seeded with the current value of the system clock to generate a random number:

Body: 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).

Random random = new Random(System.currentTimeMillis()); int accountID = random.nextInt();

Notes

Maintenance: As of CWE 4.5, terminology related to randomness, entropy, and predictability can vary widely. Within the developer and other communities, "randomness" is used heavily. However, within cryptography, "entropy" is distinct, typically implied as a measurement. There are no commonly-used definitions, even within standards documents and cryptography papers. Future versions of CWE will attempt to define these terms and, if necessary, distinguish between them in ways that are appropriate for different communities but do not reduce the usability of CWE for mapping, understanding, or other scenarios.

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