AI Sprawl: The Untested Attack Surface
Shadow AI is already inside your network — through employee chatbots, internal RAG apps, and vendor copilots that never went through a security review.
Most security teams have no way to know whether their defenses would catch an attack through these channels. The only way to know is to validate it.
Join us to explore how to treat AI as a first-class attack surface and what a CTEM-based validation approach looks like in practice.
You’ll learn:
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Rajesh Sharma
Co-Founder and Chief Architect
Rajesh has more than 20 years of experience in the security industry. He has served as Principal Engineer and Software Architect at Websense Inc (now called ForcePoint|Raytheon), Guidance Software Inc (now called OpenText), and Resolution 1 Security (now called AccessData Group Inc.); where he developed key Kernel components used in Websense Client Policy Manager; EnCase Suite of Products and R1 Endpoint Solution. Rajesh has a degree in Computer Science and Engineering from R.E.C Bhopal India.
Paul Reid
VP, Adversary Research
Paul Reid is VP of Adversary Research at AttackIQ, where he studies real-world and AI-enabled adversaries and translates their tactics into practical, testable defenses. With more than 20 years in cybersecurity, he has led threat hunting and intelligence teams at Micro Focus, and OpenText Cybersecurity, supporting governments, critical infrastructure, and large enterprises against nation-state-grade threats. He is the author of Biometrics for Network Security, holds multiple cybersecurity patents, and regularly speaks on threat-informed defense and adversary tradecraft.
William Booth
Senior Director, Product Management
William Booth is Senior Director of Product Management at AttackIQ, where he leads cybersecurity product strategy focused on helping organizations operationalize Continuous Threat Exposure Management (CTEM). Prior to AttackIQ, he served as General Manager of MITRE ATT&CK® Evaluations and previously led MITRE Caldera™. William has hands-on experience defining how ATT&CK coverage is measured, evaluated, and communicated across the industry.
Shravan Ravi
Security Data Scientist
Shravan is a Security Data Scientist at AttackIQ, where he works directly on Large Language Models (LLMs) and Generative AI initiatives in the Breach-and-Attack-Simulation (BAS) space. With 9 years of experience in the field and a Masters in Signal Processing from University of Southern California, Shravan is passionate about using data and mathematics to tackle complex, multi-tiered real-world challenges. He is dedicated to advancing the field of cybersecurity through innovative approaches and cutting-edge technology. His work at AttackIQ focuses on enhancing threat-informed defense strategies, making cybersecurity more proactive and effective.
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