This talk cuts through the vendor hype to share real-world experiences integrating AI into security workflows. We’ll explore specific use cases where LLMs genuinely improved security—from automating alert triage to synthesizing threat intelligence—and more importantly, where they failed spectacularly. You’ll learn why that “AI-powered code improvement recommendations” POC crashed and burned, and how hallucinating LLMs almost caused priority one incidents.
Learning Objectives:
- Real metrics on time savings and accuracy from production LLM deployments
- Specific use cases that work (and those that definitively don’t)
- A hands-on walkthrough of the OWASP Top 10 for LLMs with defensive coverage built by our team
- Internally developed detections and response capabilities mapped to high-priority OWASP LLM risks—prompt injection, insecure output handling, sensitive data disclosure, and more
- Critical security guardrails for protecting sensitive data in AI workflows
- A decision framework for evaluating AI tools without falling for the hype
- Practical tips for getting buy-in from leadership, legal, and your analysts
This workshop supports content and knowledge from LDR512: Security Leadership Essentials for Managers. To learn more about this course and explore upcoming sessions, Click Here.
