What is UEBA?
User and Entity Behavior Analytics
A security analytics approach that baselines normal user and device behavior, then uses statistical models and machine learning to detect anomalies indicative of compromised accounts, insider threats, or policy abuse.
UEBA ingests log data from multiple sources, including identity providers, SWG proxy logs, CASB activity records, endpoint telemetry, and authentication events, to build behavioral profiles for each user and entity (device, service account, application). Once baselines are established, the system flags deviations: a user downloading 10x their normal data volume, logging in from an unusual geolocation, or accessing applications they have never touched before.
Within SASE/SSE platforms, UEBA is typically embedded in the CASB or analytics engine rather than deployed as a standalone product. It adds a risk-scoring dimension to access decisions. For example, a user with an elevated risk score might be stepped up to additional MFA, have their session routed through RBI, or be restricted from downloading files until the anomaly is investigated.
The effectiveness of UEBA depends entirely on data quality and tuning time. Behavioral models need weeks to months of clean data to establish reliable baselines. Organizations with high employee turnover, seasonal work patterns, or frequent role changes will see more false positives. UEBA works best as an input to an existing investigation workflow rather than as a standalone alerting system.
A platform that aggregates, normalizes, and correlates security event logs from across the enterprise, providing real-time alerting, historical analysis, and compliance reporting.
A security control point between users and SaaS applications that provides visibility into shadow IT, enforces data protection policies, and detects threats across cloud services.
A security model that eliminates implicit trust based on network location, requiring continuous verification of identity, device posture, and context for every access request.
A set of technologies that detect and prevent unauthorized transmission of sensitive data by inspecting content at rest, in motion, and in use against predefined and custom data patterns.
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