Why AI Security Requires Context: Introducing Issues & the Correlation Agent

Data is never the problem. Security teams rarely complain about having too much of it. The real danger comes from data that sits unconnected and unexplained. What teams actually need is data that is actionable and converges into meaning. Data that cuts deeper than surface level signals. Data that reveals what is unfolding and what needs to happen next.

Securing AI is no different. AI agents generate endless activity and dozens of subtle insight signals. A minor misconfiguration can trigger findings that look urgent but have no real impact. Runtime anomalies appear with no surrounding context. Security teams end up chasing symptoms instead of causes, forced to investigate every notification as if it could become the one that matters. Investigations slow down, uncertainty grows, and the real signal becomes far too easy to miss.

This gap, the space between raw signals and real understanding, is now the defining challenge of AI security. And it requires a new approach.

Why AI era investigations demand a new approach

Traditional workflows assume that findings come in as isolated events with clear boundaries. AI does not behave that way. AI agents trigger chains of decisions across environments. A single prompt can start a lateral movement pattern. A seemingly harmless misconfiguration can quietly open an exposure path. And all of it happens in minutes, not hours.

When those signals arrive uncorrelated, they look identical. A medium severity alert can hide the start of an exfiltration path. A cluster of runtime anomalies can feel like noise when they are actually the first signs of manipulation. Without context or reasoning, security teams are stuck reconstructing intent from siloed data points. They waste time fighting the investigation rather than the threat itself.

The release of Issues and the Correlation Agent is meant to change that. These capabilities give security teams a way to see how signals relate, how risk moves, and what narrative sits behind the notifications.

What the new capabilities make possible

This release gives practitioners the missing context they’ve been trying to assemble manually. A way to uncover hidden relationships. A way to understand intent. And a way to move faster with confidence.

Issues take posture findings, runtime anomalies, identity relationships, and graph insights and combine them into a coherent narrative. Each incident includes the root cause, the entities involved, the attack path, the sequence of events, and the evidence analysts need to move forward with confidence. It lets practitioners begin investigations with clarity rather than spending cycles piecing together the basics.

The Correlation Agent gives teams something they have never had before, visibility into intent. A critical element that traditional detections can’t capture. It interprets behavior, surfaces manipulation attempts, and explains what the agent was actually doing - reducing guesswork and shortening time it takes to understand what is happening.

How these capabilities change day-to-day work

With Issues, investigations no longer begin with manual correlation. The narrative is already taking shape. A prompt injection attempt appears as a multi-stage attack with the relevant prompts, the downstream actions, and the impacted systems. A misconfigured connection shows up as a full exposure path, mapped visually and supported with evidence. Severity evolves in real time. When exploitation begins, the incident escalates automatically. Security teams can see the attack unfold rather than trying to reconstruct it after the fact.

This creates an investigation workflow that finally matches the pace of AI-driven environments. Practitioners spend their time validating impact and determining the right response instead of stitching together data points or rechecking the same notifications. The queue shrinks. The signal becomes clear. And teams can direct their effort toward the threats that demand action.

See it for yourself

If you want to understand how your agents behave in the real world there is no better place to start than Issues and the Correlation Agent. These capabilities reveal how posture and runtime signals converge, how identities and graph relationships shape risk, and how small vulnerabilities develop into incidents that matter. The agents in your environment are already creating stories. These capabilities finally allow you to see them.