SecRespond: Benchmarking AI Agents for Real-World Post-Compromise Incident Response

Researchers introduced SecRespond, the first benchmark for evaluating LLM agents on post-compromise incident response.

The test uses forensic disk snapshots, security alerts, scans, and baseline checks across 10 cyber ranges.

In trials of 23 frontier models, agents handled alert-driven issues but often missed silent intrusions.

Models also struggled to produce fully verified remediation plans after a host was already compromised.

The results highlight a major gap in current AI security tools: reading alerts is not the same as trustworthy forensic response.