RedHatProductSecurity

RedHatProductSecurity / prodsec-skills

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Security skills for AI coding assistants and agentic systems

11
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100% credibility
Found Apr 28, 2026 at 11 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A curated collection of markdown-based security guidelines for AI coding assistants to promote secure development, testing, auditing, and tooling practices.

How It Works

1
🔍 Discover security guides

You find a helpful collection of simple guides that teach AI coding helpers how to build safer software right from the start.

2
📥 Get the guides

You easily grab the folder full of ready-made tips on secure coding, testing, and reviewing.

3
📂 Choose a guide

You pick the perfect guide for your project, like one for preventing data leaks or checking for weak spots.

4
💬 Tell your AI to use it

You chat with your AI coding assistant and point it to the guide so it applies security smarts to your code.

5
🔧 Review or build securely

Your AI now suggests ways to make your code tougher against common dangers, feeling confident and guided.

🛡️ Safer projects every time

Your software comes out stronger and more protected, with security woven in naturally from the beginning.

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AI-Generated Review

What is prodsec-skills?

Prodsec-skills delivers 128 structured markdown files packed with security best practices for AI coding assistants like GitHub Copilot, Claude Code, and Cursor, plus agentic systems. Developers reference a skill path in prompts to get targeted guidance on secure development, fuzzing, auditing, and tooling—shifting security left during code writing and testing. Built in Python with a simple make bootstrap for pre-commit hooks and linting via uv, ruff, and ty.

Why is it gaining traction?

It stands out with tool-agnostic markdown that plugs into any assistant supporting file reads, covering AI infrastructure hardening, OAuth for MCP servers, fuzzing harnesses, and Semgrep rules without vendor lock-in. Curated from Red Hat, Trail of Bits, and CoSAI sources under Apache 2.0 and CC licenses, it offers precise triggers like input sanitization or variant analysis. Developers notice immediate wins in prompts for github security scanning, security github actions, and agentic auth.

Who should use this?

Security engineers securing AI/agentic stacks (MCP clients/servers, inference engines, RAG systems) who pair with Copilot or Claude Code. Teams fuzzing Rust/Python/C++ parsers or running static analysis via Semgrep/CodeQL in PR reviews. Devs listing security skills for resume or CV, from supply chain SBOMs to web injection defenses.

Verdict

Worth forking for AI-assisted security workflows despite 11 stars and 1.0% credibility score—docs are thorough, skills production-ready, but it's early-stage with room for community contributions. Try if you're deep in agentic assistants; skip for generic github security policy needs.

(198 words)

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