Open detection standard -- like Sigma, but for AI agents. 425 rules, shipped in Microsoft AGT, Cisco AI Defense, MISP, OWASP A-S-R-H. 97.1% recall on NVIDIA garak. NIST OSCAL Path 1.
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Jun 11, 2026 - TypeScript
Open detection standard -- like Sigma, but for AI agents. 425 rules, shipped in Microsoft AGT, Cisco AI Defense, MISP, OWASP A-S-R-H. 97.1% recall on NVIDIA garak. NIST OSCAL Path 1.
Vulntrex - View, Run & Compare Garak Scans in one sleek web interface.
Projet issu du codelab Devfest Nantes 2025 “La guerre des prompts” : atelier de 2h pour apprendre à pirater des IA et comment les protéger via des frameworks open source
Red teaming AI Goat™ to explore OWASP Top 10 for LLM Applications (2025), prompt injection, RAG poisoning, MCP-assisted auditing, and AI security vulnerabilities.
KYA (Know Your Agents) — Open-source trust, governance, and evidentiary assurance infrastructure for autonomous systems. Built on KYP (Know Your Principal), a unified trust model for human users, AI agents, service accounts, and machine identities.
Out-Of-Tree Llama Stack Eval Provider for Red Teaming LLM Systems with Garak
Production-grade LLM evaluation pipeline for RAG chatbot — DeepEval + RAGAS + Garak + CI/CD | Financial domain | 7 metrics | Adversarial testing
Iterative AI purple-team harness: 5 specialist agents under a deterministic state machine, ATT&CK + ATLAS aware. Includes reproducible findings against GPT-4o (EchoLeak-style injection, MCP tool-description poisoning) and an upstream PR for garak detector calibration drift.
Web-based GUI for Garak LLM security scanner. Test local Ollama models with an intuitive interface.
This repo consist of exploratory work related to AI pen testing using open source versions of garak, promptfoo
IA ofensiva sin censura, contenida y segura para su operador — red teaming ético asistido por IA sobre Kali.
An OWASP-LLM-Top-10-2025 red-team teaching lab
Single-file, fully-local three-layer AI red-team smoke test for LLMs + MCP servers — honest, CI-ready, not a compliance tool.
Relentlessly scanning, probing, prodding LLM endpoints. The Inquisition always gets its answers.
OPA/Rego LLM access policy (Shadow-AI control) plus a garak red-teaming config.
Adversarial testing methodology, attack simulations, and MITRE ATLAS mappings for securing clinical AI and LLM systems.
OWASP GenAI Top 10 vulnerability testing framework for LLMs — fully local, GPU-accelerated, custom guardrails
Compliance-focused vulnerability probes for NVIDIA garak, targeting LLMs in regulated industries (CMMC, NIST, HIPAA, DFARS)
Modular LLM red teaming framework for testing AI vulnerabilities through one-shot attacks via Garak or multi-turn attacks via PyRIT
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