AI vs AI: Validating Defenses Against Intelligent Threats
Generative AI is giving attackers new speed, scale, and stealth—and defenders a new layer of complexity. From deepfake phishing to automated reconnaissance, the rules of engagement are changing fast.
In this Prove It episode, CISOs Pete Luban and Jason Lord cut through the AI security noise and talk candidly about what actually works when validating defenses against intelligent threats.
You’ll hear how they’re testing their environments against AI-enabled adversaries and where they’re using AI themselves to improve detection, response, and control validation.
You’ll learn:
This session is for leaders who don’t just want to understand the threat—they want to prove they’re ready for it.
Pete Luban
Field Chief Information Security Officer, AttackIQ
Pete has nearly 30 years experience in infrastructure architecture, cybersecurity engineering and operations, and risk management acquired through various roles at many well known organizations such as Citigroup, Yahoo!, Google, Bridgewater Associates and Netflix. Pete has spent the last six years as the Chief Information Security Officer at Dimensional Fund Advisors, an 800 billion dollar asset manager headquartered in Austin Texas, and one of the worlds leading providers of ETFs and Mutual Funds.

Jason Lord
CTO & CISO, AutoRABIT
Jason is a seasoned cybersecurity executive and subject matter expert with over 30 years of experience in managing enterprise technology and security risk. His expertise spans a wide range of areas, including cybersecurity operations, cloud security, cyber intelligence, insider threat management, incident response, and penetration testing. Previously, he served as the Chief Information Security Officer at the White House and as a Departmental CISO at Bridgewater Associates. He is currently the Chief Technology Officer and Chief Information Security Officer at AutoRABIT.

Register for the Webinar
By submitting this form you indicate that you have read and agree to the terms of our Privacy Policy.
