AI is fundamentally changing how threats are created and detected. Polymorphic AI malware continuously modifies its code and evades detection by not writing to disk and running solely in memory. Even if its use is nascent, this new class of malware changes the game for threat detection, rendering traditional signature matching and static detection methods obsolete. But if adversaries can use AI, so can defenders.
View the on-demand webinar to learn how attackers are using AI in real-world attacks. Threat Researcher Liora Itkin will walk through a live polymorphic AI proof-of-concept to show how these shape-shifting threats work–and how to evolve your detection strategy to beat them. We’ll cover what it takes to go beyond static, predictable detection techniques and build threat-informed defenses for AI-powered attacks.
In this webinar you’ll learn:
- What polymorphic AI malware is and how it works, with a live proof of concept overview
- How real-world adversaries like APT28 are using these shape-shifting threats in observed attacks
- Why traditional detection approaches and tools–including some EDRs–miss these threats
- How to reframe your detection strategies to identify and defend against these AI-powered attacks
- How to fight these AI-powered attacks with your own defensive AI techniques
- How to operationalize threat intelligence on AI-powered attacks into threat-informed defenses
Featured Speaker
Liora Itkin
Senior Security Researcher
CardinalOps
Liora Itkin is a Senior Security Researcher currently working at CardinalOps, where she focuses on detection engineering and threat coverage optimization. She previously worked as a Security Researcher at Palo Alto Networks, in incident response at a leading MDR company, and in an intelligence unit—building a strong foundation in SOC operations and detection strategy. She is particularly interested in advancing detection methodologies and frequently collaborates with the security community through research and knowledge sharing.
