EthiHack — AI Red Teaming Platform

EthiHack is a full-stack AI red teaming platform that automatically discovers, exploits, and reports security vulnerabilities in large language models and AI agents. The Problem: As enterprises deploy AI agents with access to databases, email systems, APIs, and sensitive data, the attack surface has exploded. Most organizations have no way to test whether their AI is vulnerable to prompt injection, jailbreaks, data exfiltration, or tool abuse — until it's too late. What EthiHack Does: EthiHack fires. 20 adaptive multi-turn adversarial attack chains against any AI system — covering every category in the OWASP LLM Top 10 and MITRE ATLAS framework. It works against any target: OpenAI GPT, Anthropic Claude, Groq LLaMA, Google Gemini, custom webhooks, or local models. Key Features: - Phase 1: AI fingerprinting — identifies model, guardrails, identity leak vulnerabilities - Phase 2: 20 pre-built attack chains covering prompt injection, jailbreaks, data exfiltration, tool abuse, RAG poisoning, memory injection, and multi-agent pipeline attacks - Phase 3: Adaptive execution — each attack dynamically rewrites Turn 3 using the target's own words to maximize success - Phase 4: Dual-model verification using Claude Sonnet + Haiku for high-confidence findings - Professional PDF report with OWASP/MITRE tags, severity scores, business impact analysis, and remediation roadmap Live Demo: We tested EthiHack against 5 targets — a vulnerable chatbot (5/100), AI agent with tools (8/100), RAG medical system (5/100), multi-agent pipeline, and a hardened AI (95/100) — proving it can distinguish secure from insecure AI in real time. We also tested live against Groq's production LLaMA-3 API. EthiHack makes enterprise AI security accessible to any developer or security team, turning what was previously a manual expert process into a one-click automated audit.