llm-security-testing

An intentionally vulnerable OWASP LLM Top 10 training platform for AI Security, Prompt Injection, RAG Security, Agent Security, and GenAI penetration testing.

Find and fix web-app vulnerabilities in one command — SAST + DAST + AI, for devs who aren't security experts.

A hands-on AI security project demonstrating prompt injection, data exfiltration, and defense strategies in Retrieval-Augmented Generation (RAG) systems.

Multi-agent AI penetration testing system with persistent engagement state, strategic coordination, and parallel autonomous operations.

The calm guardian for AI, agent, and MCP code — a zero-dependency, OWASP-anchored AI security toolkit.

Security scanner and runtime policy gateway for MCP servers

A governed range for testing AI agent defenses: Agent Theater’s earned-trust tiers and human oversight, plus an adversarial arena that attacks each OWASP Top 10 for Agentic Applications risk. Measured results, honest gaps, and what it would take to close them.

AI Red Teaming portfolio — adversarial testing of LLMs & AI agents (prompt injection, jailbreaking, RAG exfiltration), mapped to OWASP LLM Top 10 & MITRE ATLAS. PhD Cybersecurity researcher (Springer-published) applying game-theoretic attack modeling to real AI systems.

Local-first enumeration and AI-assisted security review for pentesters and bug bounty hunters — parses Burp XML, HAR, cURL and JS.

Official implementation for M.Sc. Thesis: "Security Testing of Large Language Models via Causal Reinforcement Learning" (UniNa).

Automated LLM red-team harness with evolutionary attack generation (OWASP LLM Top-10 taxonomy) plus layered prompt-injection defenses, demonstrated on a recruiting assistant ingesting untrusted resumes

Interactive LLM Attack & Defense Laboratory for demonstrating and analyzing LLM security threats.