Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI-related security incident detection starts with knowing what AI systems are running across the organization. Without a complete, continuously updated inventory of sanctioned, shadow, and third-party AI tools, security teams cannot detect incidents involving systems they do not know exist. From there, effective incident management requires a structured response framework that connects detection to containment, investigation, remediation, regulatory notification, and governance integration. ‍

A ransomware advisory lands in your inbox before the morning standup, and the room goes quiet. The water utility's firewall logs are in one console, the endpoint alerts are in another, and the OT sensor feed lives somewhere else entirely. Everyone can see a piece of the story, but no one can see the whole incident. That's the part teams feel first. Not the theory, not the policy language, just the blunt realization that point tools don't become a program on their own.

Ivan Tsarynny, CEO of Feroot Security, joined CNBC’s The Exchange on July 31, 2026 to discuss a string of recent AI model “breakouts”—incidents where AI systems slipped past their own safety guardrails during testing—and what those incidents mean for how governments should regulate artificial intelligence.

There are a lot of reasons why organizations fail their FedRAMP audits and are denied the authorization they need to work on government contracts. We've even covered a lot of them here on the Ignyte blog in the past. One area that we haven't covered, in detail at least, is mistakes with the FedRAMP boundary. Not just the boundary, either, but with the diagrams that track and prove it.

It starts like this: a new employee joins, and your IT team jumps in to create an account, assign access, and configure permissions. Soon after, tickets start pouring in for password resets, group changes, and locked accounts. By the end of the week, your admins are juggling hundreds of small but critical identity tasks. That’s the everyday reality for IT teams managing enterprise systems.

Quick definition: Email security is the combination of technical controls, authentication protocols and user practices that protect email accounts, messages and infrastructure from unauthorized access, phishing, malware and data loss. Key takeaways.

How to evaluate your options, price the status quo, and make a decision your executive team will actually approve. A note on the numbers. The salaries, headcounts, and costs in this guide are illustrative. They're drawn to be realistic so the math works the way it does in a real budget meeting - but they're examples, not benchmarks. Replace them with your own.

Friday, July 31, 2026, is System Administrator Appreciation Day, the 27th annual celebration of the people who keep your servers running, your data safe, and your inbox free of “everything...

You know the drill. Two of you, maybe three, covering a product that a fifty-person engineering org reshapes daily. Too much surface, too few hands, and one manual pentest a year, assuming the budget survives Q3. That’s the reality autonomous pentesting for lean security teams was built for, and what forms the core of this guide.

Security findings are often forgotten in engineering queues. When a pentest report is added to Jira, it is assigned a low priority and remains in the backlog while new features, bug fixes, and refactorings are prioritized. Developers check the ticket and close it because they are unable to replicate the problem, there is no business-related information, and they do not understand how the attacker reached that point.