Raz Tel-Vered
Raz is a technological leader specializing in research and development of production grade solutions at the intersection of AI and cybersecurity. He has developed innovative solutions for addressing advanced security challenges and leveraging AI to detect and mitigate sophisticated threats.
Raz currently works at Zenity, where he focuses on defining and advancing the field of AI Agents security. With extensive hands on experience in data, AI, modern cybersecurity techniques and real world threat detection, he brings a unique blend of technical depth, innovation, and practical impact to securing AI driven environments.
Session
As AI systems become part of critical products and workflows, they introduce a new security surface where attacks happen through language. In traditional security domains, threat hunting focuses on signals such as network ports, traffic patterns, or system activity. In AI security, the signals are different. Instead of packets and processes, defenders analyze text interactions with models to identify malicious intent.
Effective threat hunting in AI systems requires more advanced tools. Signals hidden within natural language often require analyzing text using tools such as embedding models and perplexity to surface suspicious intent and anomalous behavior. In this talk we demonstrate a novel approach for conducting effective threat hunting in AI driven applications.