AI SOC Blind Spot: 23 Models Miss Silent Intrusions

New research reveals a significant blind spot for artificial intelligence in cybersecurity. A benchmark called SecRespond found that 23 top AI models failed to detect silent intrusions in compromised systems. This benchmark, published by Alibaba-NLP researchers, is the first to evaluate AI specifically for the post-compromise phase of cybersecurity. In ten simulated investigations, no AI model fully detected every intrusion, created a verified remediation plan, and closed the case. The findings show a clear limit for AI where enterprise security teams need it most. This comes as the AI security operations center market is projected to grow from over 18 billion dollars in 2026 to over 47 billion dollars by 2031. This research directly tests the premise that AI tools can handle autonomous post-compromise investigations, and the answer is a precise no. This matters because it highlights a critical gap in current AI capabilities for protecting against advanced cyber threats.