SecAppDev 2025 - AI / ML security

Large Language Models (LLMs) open up a new realm of possibilities in application development, but they also pose significant challenges. Their non-deterministic nature and broad use cases complicate testing, while unpredictable failures (“hallucinations”) and novel attack vectors (“prompt injections”) add risk.

This workshop covers LLM-based applications, highlights unique threats, and offers hands-on testing and hardening techniques. Attendees will learn to set up and secure basic LLM-driven solutions in their organizations.

Learning goal: Learn how LLM applications work and are architected, the unique security challenges they introduce, and the current best practices in LLM security—along with their limitations.

In this session, we will overview the general security landscape of AI technologies, including foundational machine learning, deep learning, and large language models.

Key takeaway: Integrating AI inevitably increases the threat landscape of a system. Understanding how AI can be exploited is key to developing effective mitigations