Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

GRC transformation is the organizational change from running governance, risk, and compliance as periodic, check-the-box paperwork to running it as continuous, AI-native cyber risk assurance measured in business outcomes. It is not a tooling upgrade. It is a change in what you are asked to prove. The old question was whether the work got done by audit time. The new question is whether risk is understood and the controls meant to manage it are working right now.

An AI agent runs as a process under whatever account launched it, and it inherits that account's access token. If the account has local admin rights, so does the agent, along with every helper process and script it spawns, an example would be Claude Desktop running under an admin account, spawning PowerShell helpers. What makes agents different from a typical privileged app is that their next action often comes from content parsed at runtime, including untrusted input.

Most cyber loss models are shaped around a breach. Records exposed, notification cost per record, regulatory penalty, credit monitoring, litigation. The arithmetic is well established and the inputs are reasonably well evidenced. ‍ Apply that model to an outage where nothing left and nothing was taken and every one of those categories returns zero. The organization was down for four days and the model reports almost no loss, which is not a calibration problem but the wrong model. ‍

An AI assistant reads four hundred documents across a tenant. Every read is logged. The application is named, the file is named, the timestamp is exact, and the access is attributed to an account that belongs to nobody. ‍ The audit trail is complete and it cannot answer the question an auditor asks. Nobody asks whether an access was recorded. They ask who reached the data and whether that person was authorized, and a shared service account answers neither. ‍

Companies rush to utilise the potential of large language models; however, every new use case of generative AI introduces attack vectors previously unknown in traditional web security. The present guide provides an overview of the official OWASP GenAI LLM Top 10 2026 list and explains the appearance of each vulnerability in practice along with mitigation recommendations.

For MSPs supporting industrial clients, business leaders responsible for operational risk and OT engineers implementing the standard, IEC 62443 is ultimately about securing OT and ICS environments without undermining availability or safety. Unplanned downtime, legacy systems that cannot be patched, air-gapped facilities with limited or no local IT support, and the need for predictable recovery are the day-to-day realities behind requests to demonstrate IEC 62443 alignment.

Computers are not safe. Even the best hardware and software products have the potential to conceal as-yet unknown vulnerabilities. And they aren’t all made that well. Many are shuffled into the world without a plan to detect, remediate, and notify users of those vulnerabilities. The EU’s Cyber Resilience Act aims to improve that situation.

CYJAX joins the UK's professional body for cyber security, reinforcing its commitment to developing cyber talent, upholding the highest ethical standards and helping strengthen the future of the profession. CYJAX is proud to announce that we have become a corporate member of the UK Cyber Security Council, the independent professional body dedicated to advancing the cyber security profession across the UK.