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- Gurucul UEBA
Gurucul UEBA
El Segundo, California, USA
What it is
Gurucul UEBA uses machine learning to learn normal behavior across users, devices, applications, servers, networks, and IoT devices, then identify unusual activity that may indicate compromise or malicious behavior. Entities receive risk prioritization scores from 0 to 100 so security teams can focus on threats. Listed use cases include insider risk, host and device compromise, lateral movement, data exfiltration, and account or credential compromise. Link Chain Analysis connects activity from AI agents, users, and entities into contextual evidence. Gurucul describes more than 5,000 machine-learning models and reports 70% fewer false positives, 58% faster investigations, and an 83% reduction in mean time to respond. Agentic AI can triage, escalate, and respond while keeping decisions transparent and critical thinking with people. Integrations include IAM, IGA, PAM, Splunk, Microsoft Sentinel, and IBM QRadar. Deployment options include on-premises, hybrid, SaaS, private cloud, GovCloud, and multi-cloud.
For and against
For
- Risk scores range from 0 to 100
- More than 5,000 machine-learning models
- Broad threat use-case coverage
- Integrates with major SIEM platforms
- Multiple deployment options
Against
- Pricing requires a request
- Behavioral baseline refines over time
- Performance figures are product-page claims
The verdict
Gurucul UEBA focuses on behavioral anomaly detection, contextual investigations, and automated response across many entity types. Its broad integrations and deployment choices may suit security operations teams, while pricing requires direct contact.
Who it suits
It is designed for SOC teams and security analysts facing advanced threats, limited activity visibility, or high false-positive rates. Organizations can choose self-hosted or cloud deployment models.
Plans and prices
Gurucul UEBA
Pricing not stated on the product page; request a demo
Read 28 Sep 2026 · gurucul.com
On the record
- Audience
- Gurucul says UEBA is designed for SOC teams and security analysts, especially at organizations facing advanced threats, limited user activity visibility, or high false positive rates.gurucul.com · read 28 Sep 2026
- Data independence
- Gurucul says UEBA can use an existing big data environment or a free Hadoop data lake and ingests events at no cost.gurucul.com · read 28 Sep 2026
- Deployment
- Gurucul describes platform deployment options including on-premises, hybrid, SaaS, private cloud, GovCloud, and multi-cloud.gurucul.com · read 28 Sep 2026
- Detection
- Gurucul says UEBA includes more than 5,000 machine learning models and reports 70% fewer false positives.gurucul.com · read 28 Sep 2026
- Integrations
- The platform integration catalog lists connectors for IAM, IGA, and PAM sources, plus SIEMs including Splunk, Microsoft Sentinel, and IBM QRadar.gurucul.com · read 28 Sep 2026
- Investigation
- Patented Link Chain Analysis stitches AI agent, user, and entity activity into a contextual case of evidence.gurucul.com · read 28 Sep 2026
- Limit on baseline timing
- Gurucul says built-in models can identify anomalies early, while the behavioral baseline refines over time as more data is collected.gurucul.com · read 28 Sep 2026
- Performance claims
- Gurucul reports 58% faster investigations and an 83% reduction in mean time to respond on the UEBA product page.gurucul.com · read 28 Sep 2026
- Purpose
- UEBA uses machine learning to learn normal user, device, and application behavior and detect unusual activity that may indicate compromise or malicious behavior.gurucul.com · read 28 Sep 2026
- Response
- The product page says its agentic AI can triage, escalate, and respond while keeping decisions transparent and critical thinking in human hands.gurucul.com · read 28 Sep 2026
- Risk scoring
- The product assigns entities risk prioritization scores from 0 to 100 to help prioritize known and unknown threats.gurucul.com · read 28 Sep 2026
- Support
- The product page links to Gurucul Support and offers a request-a-demo contact path.gurucul.com · read 28 Sep 2026
- Threat coverage
- Listed use cases include insider risk, host and device compromise, lateral movement, data exfiltration, and account or credential compromise.gurucul.com · read 28 Sep 2026
