UEBA uses behavior-based anomaly detection and machine learning to detect subtle deviations in user and entity behavior, enabling early identification and neutralization of insider threats such as account misuse, compromised credentials, and lateral movement.
By aggregating and correlating behavioral data across users, devices, and applications, UEBA provides holistic risk insights and contextual intelligence by developing an Entity Risk Score, empowering security teams with situational awareness to prioritize and respond effectively to emerging threats.
UEBA reduces alert fatigue by filtering noise and automating threat scoring and prioritization, streamlining SOC workflows. This enables analysts to focus on the most critical risks for faster, more precise investigations and incident response.
UEBA continuously learns and baselines normal user and entity behavior to detect subtle deviations that indicate insider threats and advanced attacks. This adaptive machine learning uncovers hidden risks that traditional rule-based tools miss, enabling proactive threat detection.
Aggregate risk signals from multiple sources into a single, actionable risk score per user or entity. Dynamic scoring prioritizes threats effectively, reducing alert fatigue and helping SOC teams focus on the most critical risks.
Uncover sophisticated threats spanning multiple systems by correlating behaviors across users, devices, endpoints, and cloud applications to detect complex attack patterns such as lateral movement and privilege abuse.
Empower analysts with enriched alert metadata, peer group comparisons, and historical behavioral context to boost situational awareness. Leverage visualizations like threat timelines and risk heat maps to drive faster, more confident decisions.
Leverage multiple machine learning models to continuously monitor and detect emerging threats without manual intervention. Automated prioritization ranks security events by risk level, streamlining SOC workflows and accelerating incident response.
UEBA natively integrates with Splunk’s security ecosystem to unify detection, investigation, and response workflows. This integration centralizes incident views and enhances SOC efficiency by combining UEBA’s behavioral insights with SIEM correlation rules.
User and entity behavior analytics (UEBA) uses machine learning to analyze the behavior of users, devices, and applications to detect unusual or anomalous activities that may indicate insider threats, compromised accounts, lateral movement, data exfiltration, and other advanced threats. It establishes behavioral baselines and identifies deviations to provide actionable security insights and reduce alert fatigue. UEBA enhances SOC efficiency by streamlining investigations with rich contextual intelligence and real-time risk scoring.
UEBA is natively integrated into Splunk Enterprise Security (ES) Premier. It aggregates risk across users, devices, cloud applications, and security layers to provide a comprehensive, user-centric risk score. This integration enables centralized incident views, enriched alert context, and end-to-end investigative workflows, improving threat detection, investigation, and response capabilities within the Splunk ES platform.
UEBA is included as a feature within the Splunk Enterprise Security Premier edition. It is not available as a standalone product or as an add-on to Splunk Enterprise Security Essentials. Customers interested in UEBA should acquire or upgrade to the ES Premier edition to access these advanced behavioral analytics capabilities.
UEBA detects a wide range of insider and advanced threats, including compromised user accounts (stolen credentials or unauthorized use), account misuse (accidental or deliberate privilege abuse), lateral movement across systems, data exfiltration via cloud storage, USB, email, and network vectors, malware-infected machines, and unknown or suspicious behaviors deviating from established baselines.
Splunk UBA (User behavior analytics) is a legacy standalone product that integrates with Splunk ES but requires separate management and workflows. Splunk UBA reached End of Sale in December 2025, and End of Support is in January 2027. UEBA, by contrast, is built natively into Splunk ES Premier, offering advanced unsupervised machine learning, broader behavior coverage (including users, devices, cloud, and applications), real-time risk scoring, and integrated investigation workflows. UEBA provides a more unified, efficient, and powerful security operations experience.
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