Brian Vermeer - Breaching your LLM-Powered Java Applications

LLMs accessing the database and intelligent agents that perform online purchases? The possibilities for AI in applications seem endless but so are their security and data privacy risks. In this session, we’ll address common issues such as prompt injection, key leakage, abuse of private customer data for model training, legal restrictions, and more. In addition, we will show that general security issues in your systems can also influence the behavior and outcome of LLMs. During this session, you’ll get a solid overview of the vulnerabilities to avoid, strategies to ensure data privacy compliance and best practices for building secure LLM-powered applications.