Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Measuring AI Agent Coverage Against the Gateway Log

A tool gateway reads every call that crosses it and enforces policy on each one. It is blind to whatever never traverses it, which is established and not the interesting part. ‍ The useful number is what fraction of an agent's total action surface the gateway covers. Blindness of unknown size and blindness of known size are different problems, and only the second lets you state what a gateway-based claim is worth. ‍

Fine-Tuning Is Not What Reclassifies an AI Deployer

The concern about fine-tuning is that it quietly converts a deployer into a provider, pulling in conformity assessment, technical documentation and a quality management system nobody budgeted for. ‍ The concern is misdirected. Fine-tuning is among the least likely routes to reclassification, and the route almost nobody worries about requires no training compute at all. ‍

AI Governance for Public Bodies, and Who Shares the Obligation

A public body running a high-risk AI system owes a fundamental rights impact assessment under Article 27 before first use, with the results notified to a market surveillance authority. The obligation is real and it is not yet in force. ‍ Regulation (EU) 2026/1744, in force since July 2026, deferred the section of the Act containing Article 27 to December 2027 for standalone high-risk systems and August 2028 for those embedded in regulated products.

What It Takes to Say an AI Control Reduces Loss by a Number

Saying a control reduces exposure is easy and almost always true. Saying it reduces exposure by a specific amount is a different claim, and the machinery for producing one is well established. Set a baseline from frequency and magnitude ranges, simulate, re-estimate the ranges with the control in place, simulate again, and report the difference. ‍ The method is sound. Applied to AI controls it runs into two problems, one about which term the control touches and one about what the estimate rests on.

Why AI Review Cannot Keep Up With the Decision

That human review becomes a bottleneck as agents scale is now widely observed. Five or ten agents working in parallel produce more decisions than one reviewer can evaluate, and under queue pressure the review degrades into approval without examination. ‍ The usual response is to move up a level, reviewing intents and boundaries rather than individual outputs.

The New Agent Control Standard Names the Controls, Not Their Value

The OWASP GenAI Security Project unveiled an Agent Control Standard in early September, donated to the project and aimed at runtime enforcement for agentic systems. It sets out that agents should be inspectable, traceable and instrumentable, with declarative hooks and policy enforcement across frameworks. ‍ It answers which controls belong around an agent.

Two Reporting Clocks on One AI Product, Only One Running

An AI product sold in Europe is described as facing two incident reporting duties. One under product security rules and one under AI rules, with different triggers and different deadlines. ‍ Only one of them is running. Article 14 of the Cyber Resilience Act has applied since 11 September 2026. The AI duty moved, and coverage published in the last few weeks still describes it as live. ‍

AI Governance as a Condition of Writing Coverage

Insurers are subject to AI governance rules and they are also the party asking other organizations AI governance questions as a condition of coverage. More than twenty states have adopted the model bulletin that turns AI oversight into an operational requirement for carriers, and those same carriers now send AI questionnaires to their corporate insureds. ‍ The sector facing both is well covered. What follows from it is not, and it produces something an insured can use. ‍

The AI Agent Whose Builder Already Left

Somebody in operations builds an automation inside a sanctioned platform to solve a problem in their own workflow. It works, other people come to depend on its output, and eighteen months later that person leaves. ‍ The platform still lists the automation. Nobody inherits it, because it was never anybody's asset to begin with, and the offboarding checklist has no line for a thing that was never recorded as belonging to the person departing. ‍