Curated, vendor-neutral open-source tools, standards, benchmarks and labs for AI Security Engineering, organized by lifecycle (Discover, Design, Build, Break, Defend). From the AI Security Engineers C
Open-source tools, research, standards, and best practices for securing software that AI writes, powers, and operates, curated by the AI Security Engineers Community.
This repository is created and maintained by the AI Security Engineers Community. It is vendor-neutral: every entry is judged against the same inclusion criteria, and anything affiliated with the maintainers' sponsor is labeled.
AI changes software in three ways at once. AI writes software: coding assistants and agents produce code faster than people can review it. AI lives inside software: models, retrieval, agent memory, MCP servers and skills become components with their own attack surface. AI operates software: agents call APIs, use credentials and change real systems, so deterministic permissions end up in the hands of probabilistic systems.
Developers, AppSec, cloud/IAM, AI/ML, SOC and GRC teams each own a piece. Nobody necessarily owns the security of the whole AI-native system. That ownership gap is what AI Security Engineering addresses.
AI Security Engineering is the discipline of designing, building, testing, and defending AI-native software throughout its lifecycle, combining software security, AI engineering, and adversarial thinking to manage risks introduced by AI-assisted development, AI-powered applications, and autonomous agents.
It is an engineering role at the intersection of software engineering, security engineering and AI engineering, and it does not replace existing teams. The discipline is still forming, so definitions here are proposals for the community to refine. Read more in f
From the project README.
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🛡️ Security audit CLI for Model Context Protocol (MCP) servers — scan AI agent configs for tool poisoning, rug pulls, hardcoded secrets, command injection & supply-chain risks. Pure Python, SARIF + CI
FarzamHabibi/pre-production-checklistPre-production checklists for solo founders. 4,337 items, 88% portable to any stack, 26 stack supplements — plus AI/agent security and the bugs AI coding assistants actually write.
omaekumiko2-create/kruLocal-first MCP password and credential manager for AI agents. Use passwords, API keys, SSH identities, and TOTP without exposing hidden plaintext to the model.
12122J/mcpvetMCP security scanner — vet a Model Context Protocol server before you add it to Claude Code, Cursor, or Windsurf. Grades it A–F, catching credential theft, tool-poisoning, and install-script payloads
Ed-Marcavage/awesome-security-agent-harnessesAI agents for pentesting, code audit, fuzzing, vulnerability discovery, and reverse engineering — harnesses, sandboxes, security MCP servers, benchmarks, and evals.
yagyeshVyas/VibeGuardFree security & privacy scanner for AI-coded apps. 699 rules, 76 MCP tools, 13-layer defense, zero-trust sandbox, AI firewall. Runs locally, never sends data anywhere. Scan your AI-generated app for l
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