As machine learning becomes embedded in SOC workflows, attackers are learning to exploit its weaknesses. This session explores the emerging field of adversarial AI in cybersecurity, showing how models can be evaded, poisoned, and manipulated. We’ll walk through real tactics adversaries use, from subtly engineered inputs that bypass classifiers to data poisoning that corrupts training sets. More importantly, we’ll outline defensive strategies to build resilience into your AI-driven security pipelines.

Attendees will leave with a grounded understanding of adversarial ML threats and practical steps to avoid being blindsided as AI adoption accelerates in defense tools.