A demonstration of how to extract confidential data and personally identifiable information from fine-tuned LLMs and vector embeddings. Shows how confidential data finds its way into your AI systems and presents attacks for identifying and extracting that sensitive data. This will highlight the problem of AI shadow data in RAG workflows and chat bots. The data may be monitored and protected in its primary store but is vulnerable and overlooked in the corresponding AI systems.