🐢 Open-Source Evaluation & Testing library for LLM Agents

The Python Risk Identification Tool for generative AI (PyRIT) is an open source framework built to empower security professionals and engineers to proactively identify risks in generative AI systems.

AI Red Teaming playground labs to run AI Red Teaming trainings including infrastructure.

Agentic LLM Vulnerability Scanner / AI red teaming kit 🧪

A powerful tool for automated LLM fuzzing. It is designed to help developers and security researchers identify and mitigate potential jailbreaks in their LLM APIs.

An offensive/defense security toolset for discovery, recon and ethical assessment of AI Agents

AI Red Teaming Range

AspGoat is an intentionally vulnerable ASP.NET Core application for learning and practicing web application security.

AI Security Platform: Defense (49 Rust engines + Micro-Model Swarm F1=0.997) + Offense (39K+ payloads) | 🎓 Academy: 159 lessons + 8 labs | RLM-Toolkit | OWASP LLM/ASI Top 10 | Red Team toolkit for AI

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

LMAP (large language model mapper) is like NMAP for LLM, is an LLM Vulnerability Scanner and Zero-day Vulnerability Fuzzer.

🤖🛡️🔍🔒🔑 Tiny package designed to support red teams and penetration testers in exploiting large language model AI solutions.

This is my prompts for Lakera's Gandalf challenges

AI‑driven multi‑agent red team engine for automated attack path prediction and controlled security validation.

🤖 Test and secure AI systems with advanced techniques for Large Language Models, including jailbreaks and automated vulnerability scanners.

Complete 90-day learning path for AI security: ML fundamentals → LLM internals → AI threats → Detection engineering. Built from first principles with NumPy implementations, Jupyter notebooks, and production-ready detection systems.

Hackaprompt v1.0 AIRT Agents

Autonomous Cybersecurity Operations and Red Teaming Agent

🤖 Enhance programming education by fine-tuning the Phi-3 Mini model to deliver well-structured, documented code responses, ensuring best practices in coding.