Havuz

Luvv-MCP 是一个 AI 原生的前端安全分析引擎，接入 Claude Code 后，你说一句"帮我审计这个网站"，AI 就能自动完成技术栈识别（1.8 万条规则覆盖 CMS/框架/CDN/中间件）、泄露扫描（阿里云 AK、GitHub Token、Webhook、J

Executable security regression testing for agentic applications and MCP-integrated systems.

An open library of 206 security skills for AI agents — pentest, bug bounty, CTF, reversing & defense across 23 domains, with CI-verified rou

Security-testing methodology as portable, tool-agnostic agent skills for Claude Code and any agent runtime: white-box bug hunting, AI-agent

Sentinel shows what a file would make your AI coding agent do. Static analyzer, merge gate and signed lockfile for CLAUDE.md, AGENTS.md, .cu

AI agent benchmark hackability scanner — find evaluation vulnerabilities before they undermine your results

pytest for AI agents - Autonomous red-teaming, behavioral monitoring & security testing for LLM agents

A curated collection of AI SecOps 24 SKILL.md capabilities for security work offensive security, SOC and detection engineering, cloud and Ku

Get Claude Code and other AI agents approved for use at work — deterministic guardrails on every tool call, tamper-evident audit logs, and a

Python SDK for LLM guardrails with safety classification, PII detection, prompt injection defense, and grounding checks. Protect AI applicat

Outside-in replication of Anthropic's Mythos Preview / Project Glasswing — open-source agentic vulnerability-discovery scaffold on Claude Op

Praxis Policy Engine (PPE)

Keep your sensitive credintials out of the agents you build and the coding agent you use. Test any agent with planted fake keys, or see whic

AI Firewall & LLM security toolkit - protect your AI applications from prompt injection, jailbreaks, PII leakage, and adversarial attacks

Open-source security for AI coding agents: record, detect and block at the tool boundary, with a verifiable audit trail in the SIEM you alre

Defense-in-depth security toolkit for LLM agents — taint tracking, proxy secret guard, policy engine, and red-team benchmarking

Red-team your RAG pipeline for prompt injection, source-document leakage, and cross-document smuggling, in CI. The gap between RAG eval (RAG

🤖 LLM Engineering Roadmap — Complete Developer Guide

250+ real-world TypeScript AI projects: workflows, agents, and multi-agent systems with production-ready architecture, not chatbot demos.

🛡 The reference playbook for pentesting AI chatbots & LLM-powered apps in one place. Ready-to-use payloads covering the full OWASP LLM Top 1

Autonomous AI-powered penetration testing platform. LLM-driven recon, vulnerability analysis, and exploit validation for internal & external

Open-source runtime security and execution control for autonomous AI agents. ALLOW, BLOCK, ESCALATE at the execution boundary with auditable

AI agent firewall that intercepts tool calls (file, shell, network) and enforces deterministic policies at sub-microsecond latency using CEL

Practical engineering knowledge for building and operating production AI systems — LLMs, RAG, agents, inference, evaluation, system design,

Self-hosted AI security proxy. Redact PII, block prompt injection, route to any LLM provider. OpenAI-compatible.

Self-hosted AI-assisted CTI-to-detection workbench for ATT&CK mapping, IOC/CVE intelligence, Threat Radar, malware triage, Attack Simulation

Pre-production checklists for solo founders. 4,685 items, 88% portable to any stack, 26 stack supplements — plus AI/agent security and the b

Public SDKs and integration contracts for Armorer Guard.

Trust nothing. Ship safely. — Skeptical-reading and prompt-injection defense skill for AI agents. Provenance tagging, red-flag patterns, ref

Open-source security audits for Supabase: a read-only MCP server, a CLI agent and a Claude Skill. Finds RLS misconfigurations, exposed keys

Static security review for AI agent configs (LangGraph, CrewAI, OpenAI Agents, MCP): maps source-to-tool flows and flags untrusted input tha

Runtime security for AI agents. In-process, zero dependencies, Apache 2.0.

Open-source digital forensics and incident response for AI agents (Claude Code, Codex, Cursor, Gemini, Copilot…). One command: detect → coll

See how you really use AI — X-ray your AI coding sessions locally

An OWASP-aligned intentionally vulnerable platform for learning and testing AI, LLM, RAG, MCP, and Agentic AI security.

Trust & security scanner for AI agents and MCP servers — OWASP-mapped findings, Trust Cards (A–F grades), SARIF + CI gate. Free CLI, zero te

RAG pipeline security testing toolkit - 27 techniques across 6 kill chain phases, mapped to MITRE ATLAS

The autonomous pentester that proves its findings — AI-driven, evidence-first, behind-login.

Document extraction and validation for logistics companies.

Local security proxy that keeps secrets and sensitive data out of AI requests. Supports Codex, Claude Code and more.

Runtime visibility for Python MCP servers. Captures tool calls, session lifecycle, module imports (SHA-256), and subprocess execution as str

Tamper-evident evidence and verification layer for AI agents. Verify any agent's session offline with just openssl. No cloud, no lock-in.

MCP server with 55 security intelligence tools — CVE/KEV, MITRE ATLAS+D3FEND, Sigma detection rules, email security posture (SPF/DMARC), dom

Convert public bug bounty hackerone reports (9,950) into reusable AI security skills and vulnerability knowledge.

A Claude / AI security review prompt for shipping safe apps. TRAP (True Readiness Audit Prompt) turns Claude Code, Cursor, or Copilot into a

agents that run on your claude subscription. multi-agent, sandboxed by default. polished telegram UI.

Open-source, self-hosted AI agent for terminal, Telegram and Raspberry Pi. Local Ollama or Claude/Codex workers, enforced by a deterministic

BloodHound-style risk analysis for multi-agent AI architectures. Parses CrewAI, Dify, LangGraph, or generic YAML into a typed capability gra

Deterministic governance for AI coding agents. Cedar-based policy engine that intercepts every agent action and evaluates it against determi

Open-source AI security platform providing perimeter defense for LLMs and AI agents through swarm analysis, policy enforcement, adversarial