Open source ai-security projects
Every project in the registry tagged ai-security, ranked by real GitHub adoption.
Open-source AI penetration testing tool to find and fix your app’s vulnerabilities.
Shannon is an AI pentester for web applications and APIs. It analyzes your source code, identifies attack vectors, and executes real exploits to prove vulnerabi
Security scanner for AI agent skills. Detect vulnerabilities, malicious patterns, security risks, prompt injection, data exfiltration, and supply-chain risks in
OpenAI's Codex Security CLI and TypeScript SDK for finding, validating, and fixing security vulnerabilities. npm: https://www.npmjs.com/package/@openai/codex-se
A full-stack AI Red Teaming platform securing AI ecosystems via Agent Scan, Skills Scan, MCP scan, AI Infra scan and LLM jailbreak evaluation.
🐢 Open-Source Evaluation & Testing library for LLM Agents
AI-powered bug bounty hunting toolkit that works with or without subscription.
secure multiplexed execution paths for agents - zero trust, zero setup, zero latency.
Open-source AI-powered offensive security harness for automated penetration testing.
Open-source AI-powered Security Operations Center — alert fusion, purple-team drills, agent-assisted triage, MITRE ATT&CK investigation. MIT-licensed, self-host
Turn Claude Code into your offensive security research assistant. Specialized AI subagents for authorized penetration testing plan engagements, analyze recon, r
ToolHive is an enterprise-grade platform for running and managing Model Context Protocol (MCP) servers.
Open-source, self-hosted AI vulnerability research tool that orchestrates agents to find and validate security issues in code.
Open-source AI pentester that proves every finding. Machine oracles re-run each exploit; verified bugs ship a proof capsule you can replay yourself.
ADR secures enterprise AI agents through observability, security benchmarking, and threat detection. Deployed at Uber.
Akto is the fastest growing AI Security platform for your teams to secure AI agents, MCPs, LLMs, Agent skills, Gen AI apps in your organization.
An AI-powered threat modeling tool that leverages OpenAI's GPT models to generate threat models for a given application based on the STRIDE methodology.
Autonomous AI pentesting agents — real-time reconnaissance, vulnerability detection, and exploitation orchestration. Go + TypeScript.
A security scanner for your LLM agentic workflows
Reconmap is a collaboration-first security operations platform for infosec teams and MSSPs, enabling end‑to‑end engagement management, from reconnaissance throu
A deliberately vulnerable banking application designed for practicing Security Testing of Web App, APIs, AI integrated App and secure code reviews. Features com
Open-source AI agent firewall for MCP security and agent egress. Scans mediated HTTP, MCP, A2A, and WebSocket traffic for exfiltration, SSRF, and prompt injecti
The independent security agent for AI-written software. Finds issues, investigates whether they are real, and shows you the evidence. Deterministic core, no API
Local security audit for AI API relays and LLM proxies: detects prompt injection, model substitution, tool-call rewriting, SSE anomalies, error leakage, and Web
Runtime security for AI apps and agents: prompt injection detection, tool-call authorization, sensitive-data redaction, bot protection, and rate limiting. Drop
Open-source runtime AI agent security tool - monitors and controls AI agents, catching malicious tool use, prompt injection, and policy drift in real time, befo
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Frequently asked questions
How many open source ai-security projects are there?
This registry tracks 26 projects tagged ai-security, with 186,551 GitHub stars between them. The most-adopted is strix at 63,281 stars.
Are these ai-security projects free to use?
Yes — 26 of the 26 carry an explicit open-source licence across 3 distinct licences, so there is no licence fee. Where a project also sells a hosted or enterprise version, the self-hosted path remains free.
Which ai-security project should I choose?
The list above is ranked by GitHub stars, but stars measure attention rather than fit. Check three things on each card: the licence (permissive versus copyleft), the language it is written in, and the last-push date — a high-star project that has not been pushed in a year is a liability.
Are these ai-security projects still maintained?
25 of the 26 were pushed in the last 90 days, and every card shows its exact last-push date so you can see the rest. Sort your shortlist by that date before committing to a migration.