It provides a unique live-demo experience with one-click attack scenarios, a single toggle to switch between vulnerable and secure modes, and an in-app architecture/attack flow panel designed for conference talks, all mapped to OWASP LLM and Agentic Top 10.
A fully local, self-contained RAG chatbot built to make Prompt Injection, Tool Abuse, Excessive Agency, Data Leakage, and Insecure Output Handling visible — live, in front of an audience.
⚠️ This is an intentionally vulnerable educational sandbox. It is built to demonstrate real attack techniques against a RAG chatbot, live, in a conference talk. Do not deploy it to a public or production environment. Full disclaimer in SECURITY.md.
Seven live attack scenarios, one click each, with a Secure Mode switch that
shows the exact same attack get blocked in real time — plus an in-app
Architecture view and an Attack Flow panel so an audience can follow along
without a single slide. Mapped to both the OWASP Top 10 for LLM Applications
and the brand-new OWASP Top 10 for Agentic Applications (2026).
Built as the companion sandbox for the talk "AI Runtime Security: Breaking
(and Defending) RAG Chatbots — Live" (Azure OpenAI · RAG Agents · Process &
Culture track). Slides are in /slides.
Traditional security controls protect networks, endpoints, identities, and applications. RAG chatbots and AI agents open a new attack surface: prompts become input, models become decision engines, agents execute actions, and tools get direct access to business systems. This sandbox makes five OWASP LLM Top 10 risk categories, plus one from the newly published OWASP Top 10 for Agentic Applications (2026) — ASI04: Agentic Supply Chain Vulnerabilities, via an MCP tool poisoning demo — reproducible and demonstrable in minutes, against your choice of Azure OpenAI, OpenAI, Anthropic Claude, Google Gemini, or any local OpenAI-compatible model, with zero setup cost thanks to a built-in offline mock model.
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Live RAG chatbot security demo — prompt injection, tool abuse, excessive agency
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