How Runtime Signals Reveal Attack Paths That Static Scans Miss

In general, today’s cloud security solutions focus heavily on static checks for vulnerabilities or exposed configs. These findings can be thorough, but they don’t surface live activity that turns a weakness into an attack.

That's the real gap, and it's a runtime issue, not a triage problem. A workload with no external connections during a scan might pick up three of them an hour later. Cybersecurity teams end up sitting on a pile of accurate but frozen findings, unable to tell which ones describe today's environment and which ones describe an environment that no longer exists.

Wiz recently looked at runtime activity, meaning the live connections happening between workloads at any given moment, across the environments it monitors. In one out of every six environments, that activity revealed serious attack paths that static analysis alone had missed.

The lesson isn't that vulnerability scanning is unreliable. It's that a finding without runtime context is a question mark, not an answer. Static analysis reveals what could go wrong. Runtime visibility tracks what's actually happening. Cloud security teams need both, and runtime scanning works best when it's part of the strategy from day one, not added on later.

Why Static Scans Only Show Half the Picture

Agentless scanning and posture tools catalog every vulnerability, misconfiguration, and publicly exposed asset. With enough scan cycles, teams end up with a fairly complete inventory of everything that's wrong. That type of mapping is useful, but it doesn’t answer the most important question: Can this finding turn into a real attack path at a moment’s notice?

The nature of static scanning is part of the problem. It captures a single point in time, while cloud environments rarely stay still long enough for that snapshot to hold. A container with no access to a secrets store during a scan might be granted that access the next day through a routine permissions change. By the time the next scan cycle runs, the environment has already moved on, and the findings sitting in the report may no longer reflect what's relevant right now.

It's kind of like high cholesterol versus a heart attack. High cholesterol is a real risk. It should be treated, and ignoring it is a mistake. But it is not the same thing as a heart attack happening right now. One is a condition sitting in the background. The other is an ongoing event, and it changes what you do over the next five minutes.

Runtime Signals Across Containers and Kubernetes

To answer the key question of whether a finding can turn into an attack path, security teams need a live feed of what's actually connecting to what. That added context, plus the original finding, is what turns a static risk into a confirmed attack path.

Containerized environments are good places to see why that connection matters. Let’s say an exposed container has a known vulnerability. That container also has a live connection to a database or a secrets store. On a static scan, that's three separate findings. But in runtime terms, it's one finding. One attack path, fully formed and worth immediate attention.

That is the benefit of Kubernetes runtime security. It increasingly runs on eBPF, a capability built into the Linux kernel that watches process activity, file access, and network connections directly, without installing anything on the workload itself. Across a cluster, that means visibility into DNS queries, container-to-container connections, and which pod is talking to which service.

It does so continuously, making it way more valuable than a point-in-time snapshot you would get with a traditional scan.

Agentless and Runtime Are Not Rivals

This hardly means that agentless scanning is obsolete. It’s still a great tool to maintain a full inventory and posture coverage without having to deploy specialized agents across every workload. That full-coverage visibility still holds value, and it's something that runtime monitoring doesn't replace.

The difference between agentless CNAPP and runtime protection comes down to what question each one answers. Agentless gives you broad, continuous visibility across the entire environment. It's how teams find every asset, misconfiguration, and vulnerability, without touching a single node.

Runtime protection answers a narrower but sharper question. Of everything Agentless found, what's live and connected right now? In practice, the two approaches work together to give a full picture of the attack surface.

The most effective approaches combine agentless visibility with runtime monitoring, using the former for broad coverage and the latter to validate what is actively running. For example, Wiz's "Sensor" runtime solution adds live runtime telemetry on top of agentless posture data, illustrating how these two approaches can work together to provide more complete visibility.

AI Workloads Add a New Runtime Blind Spot

AI workloads add a new wrinkle to all of this. AI agents and chatbots regularly make live outbound connections, sometimes to MCP servers, that never show up in any static config.

This raises a fair question: Do AI security systems monitor runtime activity, or do these connections slip through unnoticed?

For most tools, the answer is not yet. Some solutions, such as Wiz Sensor, have begun tracking these runtime connections by flagging an AI agent's live connection to an external MCP server for further review, similar to how security tools monitor a container's connection to a database.

As AI agents take on more autonomous tasks, this type of visibility will matter more and more.

What This Means for Cloud Security Teams

The takeaway is simple. Visibility without runtime context leaves teams guessing at what's actually urgent. A long list of vulnerabilities and misconfigurations doesn't tell you which ones matter today. It just shows what could matter, someday, under the right conditions and even then, it’s only true for the moment in which that scan’s snapshot was taken.

A finding paired with a live connection isn't a theoretical risk anymore. It's a confirmed path, and confirmed paths are what security teams should be addressing first. As cloud environments keep adding moving parts, the distinction between theoretical and confirmed will matter more than any severity score.