Chain-of-thought reasoning improves security alert triage accuracy, but requires a separate confidence calibrator trained on reasoning traces—a finetuned 30B model with reasoning outperforms larger general-purpose models without it.
This paper tackles alert fatigue in security operations by training language models to reason through cybersecurity detections step-by-step before classifying them as threats or benign.