Manager - AI Cyber Security at XBP Global
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Ravi Rajput is a Manager of AI Cybersecurity at XBP Global and a long-time offensive security researcher focused on the collision point between artificial intelligence and cyber-physical systems. His current work centers on adversarial AI, model manipulation, data poisoning, and the abuse of machine-learning pipelines in safety-critical environments—especially connected vehicles and telecom infrastructure. Ravi studies how attackers weaponize AI to scale intrusion, evade detection, and influence automated decision systems that were never designed to withstand hostile inputs.
At DEFCON 33, Ravi presented research on using LSTM-based machine-learning models to detect malicious activity on vehicle CAN networks—demonstrating how AI can serve as an intelligent defensive layer inside cars. In a separate DEFCON session, he revealed novel eSIM profile exploitation techniques that enable stealthy location tracking through weaknesses in the Android ecosystem and carrier provisioning flows.
At HITB 2024, Ravi showcased a critical browser-level exploitation path within vehicle infotainment systems that could be leveraged to pivot across internal vehicle networks and disrupt airbag ECU functionality—highlighting the real-world danger of poorly isolated automotive software stacks.
Earlier in his career, Ravi created AutoHackOS, a lightweight and widely adopted operating system built specifically for automotive penetration testing. The platform helped standardize tooling for researchers and OEM security teams, accelerating vulnerability discovery across telematics and embedded vehicle components.
Ravi is also a core member of the DEFCON Telecom Village and has delivered technical talks at DEFCON, Black Hat, HITB, Nullcon, HITCON, and multiple Bsides conferences. His research consistently explores how emerging technologies—especially AI and connectivity—reshape the attack surface of modern vehicles and mobile ecosystems.
His focus today is simple and urgent: understand how AI can be exploited before attackers do—and ensure intelligent systems do not become intelligent liabilities.
