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 comprehensive guide to adversarial testing and security evaluation of AI systems, helping organizations identify vulnerabilities before attackers exploit them.

Open-source adversary emulation for AI agents and MCP servers.

A collection of servers which are deliberately vulnerable to learn Pentesting MCP Servers.

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 adversarial testing engine, SDK, and CLI for AI agents. Runs locally or against the Humanbound Platform.

A diagnostic methodology for bypassing LLM defense layers — from input filters to persistent memory exploitation.

Open-source LLM Prompt-Injection and Jailbreaking Playground

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.

AI security and prompt injection payload toolkit

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.

llm exploitation framework

SOC-in-a-Box for AI purple teaming

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.