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

Large Language Model (LLM) agents are increasingly adopted in real-world security operations with access to host artifacts and command-line interfaces (CLIs), making it critical to thoroughly assess their security capabilities. However, existing cybersecurity benchmarks focus on pre-compromise settings where agents are placed in a clean and idealized environment before an attack occurs. This leaves the post-compromise setting underexplored. To address this gap, we introduce SecRespond, the first

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ethics.ai (29 July 2026), “SecRespond: Benchmarking AI Agents for Real-World Post-Compromise Incident Response,” evidence record 14821, https://ethics.ai/record/14821 (originally published by arXiv cs.AI).

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