CWE-1241

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
Use of Predictable Algorithm in Random Number Generator

Description

The device uses an algorithm that is predictable and generates a pseudo-random number.

Pseudo-random number generator algorithms are predictable because their registers have a finite number of possible states, which eventually lead to repeating patterns. As a result, pseudo-random number generators (PRNGs) can compromise their randomness or expose their internal state to various attacks, such as reverse engineering or tampering.

Consequences

Confidentiality — Read Application Data

Mitigations

Phase: Architecture and Design

It is highly recommended to use a true random number generator (TRNG) to ensure the security of encryption schemes. Hardware-based TRNGs generate unpredictable, unbiased, and independent random numbers because they employ physical phenomena, e.g., electrical noise, as sources to generate random numbers.

Phase: Implementation

It is highly recommended to use a true random number generator (TRNG) to ensure the security of encryption schemes. Hardware-based TRNGs generate unpredictable, unbiased, and independent random numbers because they employ physical phenomena, e.g., electrical noise, as sources to generate random numbers.