Zscaler Deception: Counter AI Attacks Without False Positives

This webinar examines how AI is reshaping cyber attacks and why traditional detection methods struggle to keep pace. The session explores how adversaries use AI agents to automate reconnaissance, code generation, and lateral movement, enabling attacks to progress across the kill chain with greater speed and effectiveness.

The discussion focuses on using deception-based security techniques to detect advanced threats without generating excessive alerts. Topics include deploying decoys, honeytokens, and breadcrumbs that convert attacker activity into actionable intelligence, improving detection accuracy while reducing false positives. Attendees will also learn strategies for defending AI infrastructure, including securing LLM environments, pipelines, and autonomous agents against emerging AI-driven threats.