Overview

The Gurucul User & Entity Behavior Analytics (UEBA) solution is an AI‑powered security platform that learns normal behavior from the start, providing real-time detection of anomalous user and entity activity. It delivers dynamic, normalized risk scores that adjust based on contextual telemetry, helping analysts distinguish real threats from false positives. With advanced machine learning and patented link‑chain analysis, Gurucul UEBA enables proactive insider threat, credential compromise, lateral movement, ransomware, and data exfiltration detection—all within the unified REVEAL analytics platform

Features and Capabilities

• Adaptive machine learning-based behavior modeling using over 3,000 pre-built and customizable models to establish accurate baselines for users and entities.
• Dynamic risk scoring engine (0–100) that continuously updates in near real-time based on behavioral anomalies and contextual changes.
• Multi-source context correlation combining data from identity, network, cloud, endpoint, and IT operations to provide enriched threat intelligence.
• Patented link-chain analysis that automatically links related indicators of compromise, building coherent case narratives for faster investigation.
• Historical behavior tracking with timeline visualization for users and entities to uncover patterns and trace attack progression.
• Immediate operational readiness with out-of-the-box use cases, dashboards, and models, while also allowing deep customization.
• Automated detection of advanced threats, including insider risks, compromised credentials, lateral movement, ransomware, and data exfiltration.
• Seamless integration with existing SIEM, SOAR, IAM, EDR, and cloud platforms for enhanced visibility and response automation.
• Scalable deployment options that support on-premises and cloud-based big data environments for flexible enterprise adoption.
• Custom machine learning development through Gurucul STUDIO, offering a visual SDK and support for importing externally trained ML models.