detecting-anomalous-authentication-patterns

What problem does it solve?

Authentication monitoring often suffers from noisy signals and slow detection of subtle compromises. This Skill leverages UEBA baselines and ML-based anomaly scoring to identify anomalous authentication patterns across identity platforms.

Core Features & Use Cases

• UEBA-based anomaly detection across Azure AD, Okta, and Windows AD logs.
• Behavioral baselines with per-user risk scoring and context-rich alerts.
• Use cases include compromised accounts, impossible travel, brute force, password spraying, and credential stuffing investigations.

Quick Start

Provide authentication logs to the Skill and it will detect anomalous login patterns using UEBA baselines and ML-based scoring.