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insufficient-randomness-anti-pattern

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Securely generate random values.

Software Engineering#code review#security#vulnerability#randomness#token generation#CSPRNG
Authorigbuend
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill addresses the critical security vulnerability of using predictable, non-cryptographic random number generators for security-sensitive values, which can lead to token forgery and system compromise.

Core Features & Use Cases

  • Identifies weak PRNGs: Detects the use of Math.random(), Python's random module, and similar predictable generators in security contexts.
  • Provides secure alternatives: Offers examples and guidance on using cryptographically secure pseudo-random number generators (CSPRNGs) like crypto.randomBytes() (Node.js), secrets (Python), and SecureRandom (Java).
  • Use Case: When reviewing code that generates session IDs, API keys, or password reset tokens, this skill helps ensure that truly unpredictable values are used, preventing attackers from guessing or deriving these sensitive identifiers.

Quick Start

Use the insufficient-randomness-anti-pattern skill to review the attached code for insecure random number generation.

Dependency Matrix

Required Modules

None required

Components

references

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: insufficient-randomness-anti-pattern
Download link: https://github.com/igbuend/grimbard/archive/main.zip#insufficient-randomness-anti-pattern

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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