Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Since we launched Certificate Transparency Monitoring in public beta in 2019, we've been emailing subscribers whenever a new TLS certificate appears in a public Certificate Transparency (CT) log for one of their domains. Today, it's turned on for more than 650,000 customer domains. It's an early warning that someone, somewhere, has issued a certificate for a hostname in your zone, giving you a chance to spot a mis-issued certificate early.

Most AI code review tools fail the same way. They work, in the sense that comments appear on the pull request. Then you read the comments and they are 80% “consider extracting this into a helper”, “missing test coverage”, “this variable name could be clearer”, and within a couple of weeks everyone has learned to scroll past anything the bot wrote. These are not false positives. They are true and irrelevant, which costs the same attention and is harder to argue with.

As a CISO advisor, I am observing a familiar pattern gaining a new, critical dimension. What we historically identified as "Shadow IT", the use of unapproved SaaS and tools, is rapidly evolving into "Shadow AI." Employees are increasingly leveraging AI bots for drafting, analysis, code generation and strategic decision-making.

Netwrix's 2026 research found a 4x gap in breach rates between organizations where AI has significantly grown their identity count and those where it hasn't. Static credentials are AI’s easiest way in: passwords, keys, and tokens that never expire and never get checked. AI didn't invent the over-privileged credential, it just found the fastest way to use one.

AI agent security is an identity problem, but it often starts as a secrets and credential problem. Do your AI agents operate using static API keys, tokens, and other reusable credentials? They might bypass traditional identity controls, creating a governance blind spot.

The OWASP GenAI Security Project published the 2026 edition of its Top 10 for LLM Applications. Prompt Injection stayed at number one. Sensitive Information Disclosure stayed at number two. Read the headlines and you would conclude that not much moved. Something did move, and it is not in the rankings. The project leads open by telling you to stop trying to build a model that cannot be fooled, and to build the system around it so that when the model is fooled, nothing important breaks.

An AI compliance audit is less mysterious than its absence from most planning suggests. Someone outside the organization reads what you wrote down, then samples real systems to test whether the organization does what the documents describe. The distance between those two things is where findings come from. ‍ Three different exercises get called an AI audit, and they run differently. Certification against a management standard follows a defined two-stage process.

Claude is moving quickly. Cato is innovating alongside it. With inference hooks, skills posture, and seamless deployment, teams can adopt new AI capabilities with security controls that are ready from day one. Claude’s rapid innovation is reshaping what everyday employees can do with AI. It is no longer just helping people write faster or summarize information; it is becoming a hands-on work companion that can research, reason, build, and take action across business workflows.

Agentic AI is crossing a threshold. It is no longer just generating content or answering questions. It is beginning to plan, decide, and execute actions across tools, systems, and workflows. That shift unlocks real efficiency, but it also changes the security equation. When an AI system can act, it becomes part of your operational attack surface. It can be influenced, misdirected, or exploited. It can make mistakes at machine speed. And if it has permissions, it can create real impact.