Agentic AI Security | case studies by Microsoft, OWASP

As promised, I’m back with Tania for a deep dive into the wild world of agentic AI security — how modern AI agents break, misbehave, or get exploited, and what real case studies are teaching us. We’re unpacking insights from the Taxonomy of Failure Modes in Agentic AI Systems, the core paper behind today’s discussion, and exploring what these failures look like in practice. We also break down three great resources shaping the conversation right now: Microsoft’s Taxonomy of Failure Modes in Agentic AI Systems — a super clear breakdown of how agent failures emerge across planning, decision-making, and action loops: https://cdn-dynmedia-1.microsoft.com/is/content/microsoftcorp/microsoft/final/en-us/microsoft-brand/documents/Taxonomy-of-Failure-Mode-in-Agentic-AI-Systems-Whitepaper.pdf OWASP’s Agentic AI Threats & Mitigations — a practical, security-team-friendly guide to common attack paths and how to defend against them: https://genai.owasp.org/resource/agentic-ai-threats-and-mitigations/ Unit 42’s Agentic AI Threats report — real-world examples of adversarial prompting, privilege escalation, and chain-of-trust issues showing up in deployed systems: https://unit42.paloaltonetworks.com/agentic-ai-threats/ Join us as we translate the research, sift through what’s real vs. hype, and talk about what teams should be preparing for next 🚨🛡️.