Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Yaniv Zimmer is an AI researcher at Torq, focusing on cybersecurity research at the crossroads of artificial intelligence, deep learning, and defensive operations. Drawing on extensive experience within Unit 8200 alongside industry and academic AI research roles, his work centers on advancing SOC AI architectures and threat detection capabilities Like a lot of people, we were excited when Jev launched. The premise is genuinely useful in production: an intelligent language model built for classification.

There’s been a lot of buzz lately about using AI to automate Tier 1 and Tier 2 SOC work. Anthropic, using Claude as the base, has been leading with some of the most specific “how to” research.

Over the course of this series, I’ve laid out the case for a fundamentally different security operating model — one built around Outcome, Judgment, and Execution layers, where AI handles the execution at machine speed, and humans focus on the decisions that actually need them. I’ve argued that the CISO’s role is changing, that human-centric security no longer scales, and that the org chart needs to reflect where AI fits on the team.

John White is the Field CISO for EMEA at Torq. A respected security executive with more than 20 years of leadership experience, John previously served as CISO at Virgin Atlantic, where he led a multi-year transformation deploying the Torq AI SOC Platform to modernize cyber operations. Prior to that, he built and transformed security functions for global organizations, including ASOS, Liberty Global, AEG Europe, and KPMG.

The average adversary breakout time is now 29 minutes, with the fastest recorded at 27 seconds, according to the CrowdStrike 2026 Global Threat Report. AI is supercharging the adversary playbook, empowering many to move faster across multiple domains. Defenders must match that speed with AI-driven security operations that investigate and respond across every domain, in real time.