Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

A cyber risk register is a centralized, continuously updated record of every cybersecurity threat, vulnerability, and scenario an organization is tracking, structured so security, risk, and executive teams can prioritize, quantify, and act on each entry. Done well, it becomes the operational backbone of the cyber GRC program, translating technical security data into the business language leadership needs to make investment decisions.

The enterprise AI security market in 2026 is crowded and confusing. Vendors that built their products to use AI for cybersecurity operations now market themselves alongside vendors that built their products to secure AI systems and govern AI usage. These are fundamentally different product categories solving different problems, and conflating them leads to evaluation errors that leave organizations protected against external threats but exposed to the risks their own AI systems introduce. ‍

For a long time, compliance meant paperwork. Fill out the right forms, pass the annual audit, file it away. Done. Now, your development pipeline is generating code at a pace no human team can review manually, your supply chain runs three layers deep into open-source packages and AI plugins you didn’t choose, and regulators are watching in real time. The old approach doesn’t just underperform; it creates a false sense of security.

TL;DR: AI security testing solutions find vulnerabilities in code, dependencies, and AI components across the dev pipeline.

When the IT specialist at a company of 20 to 30 people left, the responsibility landed with an employee who had little technical experience. “I’m not really an IT person,” they wrote on Reddit. “I have zero coding skills.” Yet over a single weekend, they vibe-coded an entire IT support system from scratch, in an effort to streamline a process they found cumbersome. Until then, employees had submitted tickets through a Google Form, which sent their answers to a spreadsheet.