blue · Medium · 190 XP · 4 hours

AI for Threat Detection

Discover how machine learning and artificial intelligence are applied in modern SOCs to analyze network logs, flag anomalies, and prevent zero-day attacks.

Tactical attack scenario

An advanced persistent threat (APT) is moving laterally through the network. Train an anomaly detection model to detect outlier traffic and stop the breach.

Learning objectives

Understand machine learning concepts for network security
Preprocess massive log feeds for behavioral analysis
Build anomaly detection baselines to flag unauthorized pivots
Configure automatic playbooks to block malicious IPs

Recommended background

Basic terminal use and familiarity with the topic area are helpful.

Estimated duration: 4 hours.

This public overview contains no flags, credentials, or solution steps. Practise only in the provided authorized environment.