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

Description

This vulnerability occurs when software uses a pseudo-random number generator (PRNG) that is not cryptographically strong for security-sensitive operations, such as generating keys, tokens, or initialization vectors.

Extended Description

Using a non-cryptographic PRNG in a security context can expose your application to attacks. Attackers can often predict or reproduce the generated numbers, allowing them to forge sessions, decrypt data, or bypass authentication. This happens because these generators prioritize speed and efficiency over the unpredictability required for secure cryptography. Developers sometimes choose weaker PRNGs for performance reasons or because they are readily available in standard libraries. However, features that make these PRNGs efficient—like small internal states or deterministic seeding—are the same features that make them easy to break. For any security-related function, you must use a cryptographically secure pseudo-random number generator (CSPRNG) designed to withstand such analysis.

Common Consequences 1

Scope: Access Control

Impact: 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.

Detection Methods 1

Automated Static AnalysisHigh

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.)

Potential Mitigations 1

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.

Demonstrative Examples 1

ID : DX-102

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

Code Example:Bad
Java
java

Code Example:Bad
C
c

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 Predictable Seed in Pseudo-Random Number Generator (PRNG) (Predictable Seed in PRNG).

Observed Examples 5

CVE-2021-3692PHP framework uses mt_rand() function (Marsenne Twister) when generating tokens

CVE-2009-3278Crypto product uses rand() library function to generate a recovery key, making it easier to conduct brute force attacks.

CVE-2009-3238Random number generator can repeatedly generate the same value.

CVE-2009-2367Web application generates predictable session IDs, allowing session hijacking.

CVE-2008-0166SSL library uses a weak random number generator that only generates 65,536 unique keys.

References 2

The CLASP Application Security Process

Secure Software, Inc.

2005

https://cwe.mitre.org/documents/sources/TheCLASPApplicationSecurityProcess.pdf(2024-11-17)

ID: REF-18

24 Deadly Sins of Software Security

Michael Howard, David LeBlanc, and John Viega

McGraw-Hill

2010

ID: REF-44

Likelihood of Exploit

Medium

Applicable Platforms

Languages:

Not Language-Specific : Undetermined

Modes of Introduction

Architecture and Design

Implementation

Related Weaknesses

ChildOf:

Use of Insufficiently Random Values (CWE-330)

ChildOf:

Use of Insufficiently Random Values (CWE-330)

Taxonomy Mapping

CLASP
CERT C Secure Coding

Notes

MaintenanceAs 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.