Gurucul UEBA is a User and Entity Behavior Analytics solution that monitors and analyzes user and entity activities to detect anomalous behavior indicative of security threats. The solution establishes baseline behavior patterns from day one and uses over 3,000 machine learning models to identify deviations from normal activity. The platform provides dynamic risk scoring that adjusts in near real-time, normalizing risk scores from 0-100 based on behavioral deviations and contextual telemetry. It cross-validates anomalies against identity, network, cloud, security, and IT operations data from multiple sources and formats to distinguish false positives from genuine threats. Gurucul UEBA uses Link Chain Analysis to automatically correlate threat information and context, creating comprehensive evidence cases for security analysts. The solution presents historical timelines of entity and user activities with associated risk scores to streamline threat detection, investigation, and response. The platform addresses security challenges including insider threats, compromised credentials, zero-day exploits, advanced persistent threats, ransomware, data exfiltration, lateral movement, and account compromise. It operates on the REVEAL unified data and security analytics platform, which provides visibility across the entire IT estate regardless of data source or location. The solution includes prepackaged content and is customizable to meet specific enterprise requirements.