Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The AI Agent Attack Kill Chain: Which Stages You Can Actually Detect

The early stages of an AI agent attack are silent. The poisoning, the hijacked intent, the reconnaissance: none of it executes, so none of it produces a runtime signal, and the kill-chain instinct every security team runs on says exactly the wrong thing here: break the earliest link. There is no early link to break. You cannot detect a stage that emits nothing.

Tool Call Analysis for AI Attack Detection: Reading What Rides Inside the Call

A compromised agent doesn’t make a single call it isn’t allowed to make. It queries a table it’s authorized to read, calls a tool it’s authorized to use, sends to a domain that’s on the allowlist. Every call is legal. The attack is in the values it passes, and your tool-call log records all of it as a clean day’s work. A tool call has two layers. Almost every tool you run reads the first one: the call itself: which tool, in what order, at what rate.

How to Tell If Your AI Agent Has Been Compromised (When Every Symptom Looks Normal)

Your AI agent just did something it has never done. It called a tool that is not in its usual set, or it opened a connection to a destination you do not recognize, or its output came back subtly wrong. So you do what anyone does: you search for what a compromised agent looks like, and you find a checklist. Unusual tool usage. Unexpected data access. Out-of-context responses. Elevated resource consumption.

Compliance and Regulation Heat Up in 2026: A New Phase of Scrutiny for Financial Services Organisations

The regulatory landscape facing financial services in 2026 is more complex, more demanding, and faster moving than at any point in the past decade. Across the UK, regulators are attempting to strike a delicate balance of stimulating economic growth while maintaining strong consumer protection and financial stability. This balancing act is unfolding against a backdrop of sluggish economic performance, geopolitical uncertainty, and political pressure for "pro-growth" regulation. The result is a regulatory environment where the pace, scope, and intensity of change is accelerating sharply.

Introducing Agentic Exposure Validation

Check Point Agentic Exposure Validation (AEV) uses AI agents to reason like an attacker across your external footprint. It correlates your assets with live threat intelligence, exploit research, and attacker behavior, and tells you, in minutes, what's actually exploitable and what isn't. No assumptions. No noise. Evidence-backed findings your team can act on immediately.

Detecting AI Agent Lateral Movement in Kubernetes

An AI agent moving laterally through a Kubernetes cluster does not look like an intrusion. There is no foreign process, no exploit, no dropped binary — just the agent using the identity, network routes, and tools it was handed at deployment to reach targets it was technically allowed to touch. That is the entire problem. The controls you run were built to catch an outsider pivoting from host to host.

Commercial vs Open Source AI Attack Detection Tools: A Buyer's Guide

If you’re weighing open source against commercial tools for detecting attacks on your AI agents, you’re probably trying to answer a single question. Can we build this ourselves, or should we buy it? It’s a fair question, and the existing content on it isn’t much help. Most comparisons line up tools side by side and tally features. That tells you which tool is better at one slice of the problem. It doesn’t tell you whether you have a working detection program.

Building SecOps that improve with every frontier AI release

CEO Maxime Lamothe-Brassard made an observation after the RSA conference that security vendors don't typically say out loud: "The frontier models are just better than anything people roll their own. There's no secret sauce these vendors are offering that is better than the latest frontier model release." That's a pointed claim that carries a significant implication buyers may not have fully considered.