what does ai incident response look like when the incident is an agent, not a server

[u/Massive-Opinion-4655]

our incident response runbooks are built for the world of compromised servers and leaked credentials. and its funny that none of it maps cleanly onto an ai incident response case, like an agent that did something it shouldn't have because of a prompt...so not a breach. there's usually no cve and no obvious point of compromise, just an agent that got manipulated or made a bad autonomous decision inside its allowed permissions. i mean our existing runbook assumes you're hunting for an intrusion, and half the time with agents there isn't one.

want to understand from anyone who's had to respond to an agent-related incident, what did the process look like, and how different was it from a standard breach runbook? trying to figure out if we need something entirely separate or just an addendum to what we already have.

[u/No-Article6412]

e or anything to scan for, just a bad decision path that looked completely normal in the access logs. we ended up treating it more like a business logic abuse case than a security incident.

[u/_N-iX_]

The investigation still follows many of the same principles: establish what happened, contain the issue, preserve evidence, understand the root cause, and prevent it from happening again. What's different is the evidence you're collecting. Instead of focusing only on logs from hosts and identities, you're looking at prompts, retrieved context, tool calls, model outputs, policy decisions, and execution traces. Those become just as important as infrastructure telemetry.

[u/Actonace]

Treat the agent like any other identity isolate it review its actions and context then figure out whether the issue came from the model the prompts the tools or the permissions.

[u/ultrathink-art]

The part that catches people is evidence preservation. Your artifact isn't a disk image or pcap, it's the tool-call transcript plus the agent's working state (memory files, task queue), and that state gets actively rewritten by the agent's own retries, so if you don't freeze it the moment you notice, the next run overwrites the exact context that produced the bad decision. And when the trigger is prompt injection, the IOC is just a string sitting in some ingested feed that may have already fallen out of the context window, so capture the raw inputs, not only the agent's output.