Your scanner finds 400 CVEs in a container image. A handful are actually exploitable. The rest is noise your team patches anyway.

So I gave that backlog to my AI agent. Working from a Trivy scan, it:
1. reads the reachability graph onto which vulnerable functions your code actually calls
2. decides what's genuinely exploitable
3. writes the verdict as OpenVEX, signed and attested with in-toto and Sigstore

This talk is the honest report: what the agent got right, what it got dangerously wrong, and the human-in-the-loop design that keeps a confident LLM from waving through a live CVE.

We'll build the full pipeline on Kubernetes: Trivy scan, reachability, agentic triage, OpenVEX, in-toto/Sigstore signing, and a deployment gate with real before/after numbers on the noise it removes.

You'll leave with a pattern for cutting CVE noise with reachability and VEX, and a clear-eyed view of where an agent belongs in security work and where it absolutely does not.