A full-stack AI Red Teaming platform securing AI ecosystems via OpenClaw Security Scan, Agent Scan, Skills Scan, MCP scan, AI Infra scan and LLM jailbreak evaluation.
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Updated
Jun 25, 2026 - Python
A full-stack AI Red Teaming platform securing AI ecosystems via OpenClaw Security Scan, Agent Scan, Skills Scan, MCP scan, AI Infra scan and LLM jailbreak evaluation.
AI Red Teaming playground labs to run AI Red Teaming trainings including infrastructure.
A security scanner for your LLM agentic workflows
A collection of servers which are deliberately vulnerable to learn Pentesting MCP Servers.
A comprehensive guide to adversarial testing and security evaluation of AI systems, helping organizations identify vulnerabilities before attackers exploit them.
Whistleblower is a offensive security tool for testing against system prompt leakage and capability discovery of an AI application exposed through API. Built for AI engineers, security researchers and folks who want to know what's going on inside the LLM-based app they use daily
AspGoat is an intentionally vulnerable ASP.NET Core application for learning and practicing web application security.
Open-core AI red teaming and offensive AI security evaluation platform.
Code scanner to check for issues in prompts and LLM calls
Open-source LLM Prompt-Injection and Jailbreaking Playground
A diagnostic methodology for bypassing LLM defense layers — from input filters to persistent memory exploitation.
Open-source AI agent red-team engine, SDK, and CLI. Run offline or against the Humanbound Platform.
AI security and prompt injection payload toolkit
This document curates open-source projects, academic papers, capability benchmarks, and commercial solutions (international & China) in AI penetration testing, LLM red teaming, autonomous offensive agents, and vulnerability discovery—aimed at helping researchers, security engineers, and enterprise decision-makers quickly form a holistic view.
Awesome LLM security tools, research, and documents
Basilisk — Open-source AI red teaming framework with genetic prompt evolution. Automated LLM security testing for GPT-4, Claude, Grok, Gemini. OWASP LLM Top 10 coverage. 32 attack modules.
Comprehensive taxonomy of AI security vulnerabilities, LLM adversarial attacks, prompt injection techniques, and machine learning security research. Covers 71+ attack vectors including model poisoning, agentic AI exploits, and privacy breaches.
SOC-in-a-Box for AI purple teaming
The ultimate OWASP MCP Top 10 security checklist and pentesting framework for Model Context Protocol (MCP), AI agents, and LLM-powered systems.
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