Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Earlier this year, BlueVoyant adopted a new detection strategy built on the Advanced Security Information Model (ASIM). For those unfamiliar, ASIM is Microsoft's normalisation layer that standardises log data across products into consistent schemas. Our approach is simple: The result? Dramatically faster use case development and cleaner, more maintainable detection logic.

Most teams buy detection on a single number. The datasheet says “millisecond detection,” the proof-of-concept fires the instant a test payload lands, and the box gets checked. Then a real AI agent incident runs in production, and the postmortem shows the attack completed its objective well before anyone contained it, even though the alert, technically, fired in milliseconds. The number was real. It just measured the wrong thing.

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.

Two recent industry reports validate CrowdStrike’s leadership in the identity threat detection and response (ITDR) market: Identity is the front line of modern cyberattacks. Today’s adversaries log in and use legitimate identities to move laterally, escalate privileges, and operate inside legitimate sessions as trusted users.

Continuous threat exposure management, or CTEM, is a five-stage program framework for continuously reducing real-world security exposure. It builds on vulnerability scanning by adding risk-informed prioritization, validation of exposure conditions and control effectiveness, and cross-team mobilization to drive remediation.