Security alerts are noisy, repetitive, and time-consuming for engineering teams to triage. This lightning talk shows how small, focused AI models can be used to automate threat triage and prioritisation in real-world engineering environments.

Drawing from my work on heuristic-based malware detection, I’ll demonstrate how engineers can apply AI scoring to logs, alerts, and events to automatically classify severity, suppress false positives, and highlight genuinely suspicious behaviour. The talk focuses on simple, deployable techniques—feature scoring, rule + ML hybrid logic, and confidence thresholds—that fit naturally into engineering workflows.

This session is about AI doing useful work, not replacing engineers: reducing alert fatigue, speeding up response, and allowing teams to focus on what actually matters.