Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Integrating artificial intelligence into cybersecurity has fundamentally changed vulnerability research – and not necessarily for the better. For decades, discovering and verifying Common Vulnerabilities and Exposures (CVEs) required deep technical expertise, creating a disciplined process that kept disclosure volume relatively manageable. Today, Generative AI has obliterated that barrier to entry.

Shadow AI refers to the use of artificial intelligence tools, applications, models, or AI-powered features without the organization's required IT approval, security review, or governance. It is often associated with employees using personal accounts for tools such as ChatGPT or Gemini. However, Shadow AI extends well beyond public AI chatbots.

Endpoint visibility is the ability to identify connected devices, understand their activity and health, and assess their security posture. Without it, IT teams struggle to determine which endpoints access business resources, identify security weaknesses, and investigate operational problems. Remote employees, personal phones, contractors, cloud-connected systems, and specialized equipment expand the endpoint landscape.

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 Virgin Atlantic, he built and transformed security functions for global organizations, including ASOS, Liberty Global, AEG Europe, and KPMG.

AI used to live in a browser tab. Today it also runs inside the apps employees use every day, like Copilot in Word, in dedicated apps like ChatGPT and in coding agents such as Claude Code, Codex and Cursor. Coding agents work differently from chat apps. A chat app answers a question and waits. A coding agent is given tools and takes actions on its own, with the developer’s access. So every endpoint is becoming an agentic endpoint.

“We don’t train on your data” does not mean “we don’t retain it.” Neither promise tells you where your data is processed. Zero data retention (ZDR) closes one of those gaps. It does not close all three.

TrustCloud showed up across the security and analyst landscape in recent months. CEO Sravish Sridhar published three columns in SecurityWeek and SC Media on why point-in-time assurance no longer holds up, and both IDC and 451 Research covered TrustCloud’s continuous, AI-native approach. The pieces come at it from different angles, but they land on a common point: boards and buyers increasingly want proof a control is working now, not a snapshot from last quarter.

Originally published by the PGA of America. Operating a golf facility means keeping track of a lot more than what’s happening on the course. Tee times, lesson schedules, payroll and vendor payments all depend on technology working as it should. Keeping those systems secure is easy to put off when everything is running smoothly, but it’s worth making time before a problem interrupts the day.

The Journey to Autonomous DLP · Context Intelligence Understand the content and the boundary first. History is a secondary factor. Our vision for Autonomous DLP starts with understanding data well enough to make the right decision in real time. What does the document contain? Does it hold the user’s own information, someone else’s records, or confidential company material?

India’s largest bank confirmed a data loss incident in a 21 October 2026 filing with the BSE and NSE. The alert came five days earlier, on 16 October, through SBI’s threat intelligence channels, which its filing names alongside the Defence Cyber Agency, and from CERT-In. Both flagged suspected customer data on the dark web.