Top 6 Identity Analytics Platforms for Detecting Insider Threats in 2026

Traditional perimeter security assumed that threats came from outside the network. Modern reality is different — compromised credentials, malicious insiders, and lateral movement within trusted networks account for a significant portion of breaches. Identity analytics platforms address this by applying machine learning and behavioral analysis to identity data, detecting anomalous access patterns that rule-based systems miss.

These platforms ingest authentication logs, access events, privilege usage data, and contextual signals to build behavioral baselines for every identity in your organization. When behavior deviates from the baseline — an employee accessing systems they never use, logging in from an unusual location, or escalating privileges abnormally — the platform generates risk-scored alerts that security teams can investigate and respond to.

Identity analytics sits at the intersection of IAM and security operations, often deployed as User and Entity Behavior Analytics (UEBA) modules within broader SIEM platforms or as standalone identity threat detection solutions. This guide evaluates the six leading platforms to help you detect identity-based threats before they become breaches.

Evaluation Criteria

We assessed each platform across these dimensions:

• Behavioral Modeling: How sophisticated are the machine learning models for baselining and anomaly detection?
• Identity Context: Does the platform correlate identity data across HR systems, directories, IAM platforms, and access logs?
• Threat Detection Coverage: What identity-specific threats are detected — compromised credentials, privilege abuse, lateral movement, insider threats?
• Risk Scoring: How are risk scores calculated, and how actionable are they for security analysts?
• Investigation Workflow: What tools are available for analysts to investigate identity-based alerts?
• Integration Breadth: How many data sources and IAM platforms can the solution ingest from?
• Response Automation: Can the platform automatically respond to threats (disable accounts, revoke sessions, trigger MFA)?

1. Gurucul

Best For: Large enterprises needing a purpose-built identity analytics platform with advanced machine learning, open architecture, and identity-centric threat detection.

Overview

Gurucul is a pure-play identity analytics platform that was purpose-built for identity threat detection from its inception. Unlike SIEM vendors that added UEBA as a module, Gurucul's entire architecture is designed around identity-centric risk analysis, with over 2,500 machine learning models focused on detecting identity-based threats.

Gurucul's STUDIO platform provides a unified analytics engine that ingests data from IAM systems, HR platforms, cloud services, network devices, and endpoints, correlating all activity to identities. The platform's open data lake architecture means you own your data and can use it with other analytics tools.

Key Features

• 2,500+ ML Models: Pre-built machine learning models covering identity threats, privilege abuse, data exfiltration, account compromise, and more.
• Identity-Centric Risk Engine: Continuously calculates risk scores for every identity based on behavioral baselines, peer group analysis, and threat intelligence.
• Open Data Lake: All collected data is stored in an open-format data lake (Apache Hadoop/Spark) that customers own and can query independently.
• Peer Group Analytics: Compares individual behavior against dynamically computed peer groups based on role, department, and access patterns.
• Access Outlier Detection: Identifies excessive or anomalous access entitlements by comparing actual access against role-based expectations.
• SOAR Integration: Automated response playbooks that can disable accounts, revoke sessions, or escalate to identity governance workflows.

Pricing

Gurucul pricing is based on the number of identities monitored and data volume ingested. Enterprise deployments typically start at $50,000-100,000 per year. Custom pricing is required for all deployments.

Pros

• Most comprehensive identity-focused analytics platform in the market
• Open data lake architecture avoids vendor lock-in for stored data
• Peer group analytics provides context that reduces false positives
• Access outlier detection bridges identity analytics and identity governance

Cons

• Complex deployment requiring dedicated analytics expertise
• Premium pricing puts it out of reach for smaller organizations
• UI can feel overwhelming due to the depth of analytics capabilities
• Requires significant data integration effort to achieve full value

2. Securonix

Best For: Enterprises seeking a cloud-native SIEM with built-in UEBA that excels at detecting insider threats and identity compromise.

Overview

Securonix is a cloud-native security analytics platform that combines SIEM and UEBA capabilities in a unified solution. The platform's identity analytics capabilities are deeply integrated into its threat detection engine, using behavioral profiling, machine learning, and threat chain modeling to identify identity-based attacks across their entire kill chain.

Securonix distinguishes itself through its threat chain approach, which stitches individual anomalous events into complete attack narratives. Rather than alerting on isolated events, the platform identifies sequences of behavior — initial access, privilege escalation, lateral movement, data access — that together indicate a coordinated attack.

Key Features

• Threat Chain Modeling: Correlates individual anomalous events into complete attack narratives, reducing alert fatigue.
• Behavioral Peer Groups: Automatically groups users by role, department, and behavior patterns for contextual anomaly detection.
• Risk Scoring with Decay: Risk scores increase with anomalous behavior and decay over time if behavior normalizes.
• Cloud-Native Architecture: Built on Snowflake's data cloud, providing elastic scalability and long-term data retention.
• Pre-Built Threat Content: Hundreds of pre-built threat models for insider threats, account compromise, privilege abuse, and data exfiltration.
• Autonomous Threat Sweeper: Continuously re-evaluates historical data against new threat intelligence and detection models.

Pricing

Securonix pricing is based on data ingestion volume, typically measured in GB per day. Cloud SIEM+UEBA pricing generally starts around $50-70 per GB per day for annual commitments. Enterprise pricing with dedicated infrastructure is available.

Pros

• Threat chain approach reduces false positives and provides actionable attack narratives
• Cloud-native on Snowflake provides virtually unlimited scalability and retention
• Risk score decay mechanism prevents stale alerts from dominating analyst queues
• Autonomous Threat Sweeper retroactively applies new detection logic to historical data

Cons

• Pricing based on data volume can be unpredictable and expensive at scale
• Full SIEM+UEBA platform may be overkill if you only need identity analytics
• Migration from existing SIEM requires significant planning and data source reconfiguration
• Snowflake dependency introduces a third-party infrastructure dependency

3. Exabeam

Best For: Security operations teams needing an AI-driven SIEM with strong identity-based investigation timelines and automated response.

Overview

Exabeam provides a security operations platform combining SIEM, UEBA, and SOAR capabilities with a particular strength in identity-based investigation. The platform's Smart Timelines feature automatically reconstructs the complete activity history for any user or entity, giving analysts a chronological view of every authentication, access, and action associated with an identity.

Exabeam's behavioral analytics engine profiles every identity across hundreds of behavioral dimensions, detecting deviations that indicate compromise, insider threats, or policy violations. The platform's AI-driven approach reduces the manual effort required for alert triage and investigation.

Key Features

• Smart Timelines: Automatically reconstructed activity timelines for any user or entity, showing every relevant event in chronological order.
• Behavioral Analytics Engine: Profiles identities across hundreds of dimensions including login patterns, resource access, privilege usage, and data movement.
• Threat Intelligence Integration: Correlates behavioral anomalies with external threat intelligence for enriched risk assessment.
• New-Scale SIEM: Cloud-scale SIEM architecture with 1-year hot data retention and 7+ years of searchable cold storage.
• Pre-Built Playbooks: SOAR integration with pre-built playbooks for common identity threats (account compromise, privilege abuse, impossible travel).
• Lateral Movement Detection: Identifies unusual system-to-system access patterns that indicate post-compromise lateral movement.

Pricing

Exabeam pricing is based on the number of users and entities monitored. The cloud platform typically starts at $15-25 per user per month for SIEM+UEBA capabilities. Enterprise pricing with dedicated support and custom retention is available.

Pros

• Smart Timelines are the best investigation tool for identity-based incidents
• Per-user pricing is more predictable than volume-based models
• Strong lateral movement detection for post-compromise scenarios
• Pre-built SOAR playbooks accelerate response to identity threats

Cons

• Platform has undergone significant architectural changes (LogRhythm merger), creating transition uncertainty
• Full platform adoption requires displacing existing SIEM, which is a major undertaking
• Behavioral analytics accuracy depends heavily on the quality and completeness of ingested data
• Advanced customization of analytics models requires data science expertise

4. LogRhythm

Best For: Mid-market organizations needing an on-premises or hybrid SIEM with integrated UEBA and prescriptive investigation workflows.

Overview

LogRhythm provides a SIEM platform with integrated UEBA capabilities through its AI Engine and User/Entity Analytics modules. The platform is particularly strong in mid-market and government deployments where on-premises data residency is required and where prescriptive investigation workflows help security teams with limited staff handle complex identity threats.

Following its merger with Exabeam, LogRhythm continues to serve customers who prefer its on-premises deployment model and structured investigation approach. The platform provides SmartResponse automation for common identity threats and Case Management for tracking investigations through resolution.

Key Features

• AI Engine: Pattern-based and statistical analytics engine that detects identity anomalies including impossible travel, unusual access times, and privilege anomalies.
• User and Entity Analytics: Behavioral profiling with risk scores for users and entities, surfacing the highest-risk identities.
• CloudAI: Cloud-hosted analytics that augments the on-premises deployment with advanced ML models.
• SmartResponse: Automated response actions triggered by analytics rules — disable accounts, force password reset, quarantine endpoints.
• Case Management: Built-in case management for tracking identity investigations from alert through resolution.
• Prescriptive Procedures: Step-by-step investigation procedures that guide analysts through identity threat investigation.

Pricing

LogRhythm pricing varies by deployment model. On-premises perpetual licensing starts around $25,000-50,000 with annual maintenance. Cloud and subscription models are available with pricing based on log volume. UEBA capabilities are included in the base platform.

Pros

• Strong on-premises deployment option for organizations with data residency requirements
• Prescriptive investigation procedures reduce the expertise required for identity threat analysis
• SmartResponse automation handles common identity threats without analyst intervention
• Integrated case management keeps investigations organized

Cons

• Analytics capabilities are less sophisticated than Gurucul or Securonix
• On-premises model requires infrastructure investment and maintenance
• Merger with Exabeam creates product roadmap uncertainty
• Behavioral profiling depth is limited compared to purpose-built UEBA platforms

5. Microsoft Sentinel

Best For: Microsoft-centric organizations needing a cloud-native SIEM with identity analytics powered by Microsoft's threat intelligence and Entra ID integration.

Overview

Microsoft Sentinel is a cloud-native SIEM and SOAR platform built on Azure that includes UEBA capabilities with deep integration into Microsoft's identity ecosystem. Sentinel's identity analytics leverage data from Entra ID, Microsoft 365, Defender for Identity, and Defender for Cloud Apps to detect identity-based threats with uniquely rich context from the Microsoft stack.

Sentinel's UEBA module automatically builds behavioral profiles for users and entities based on data from connected sources, detecting anomalies in authentication patterns, resource access, and privilege usage. The platform's strength is the depth of identity signal available from the Microsoft ecosystem — sign-in risk, conditional access decisions, device compliance, and application usage — all correlated into identity risk assessments.

Key Features

• Entra ID Integration: Native ingestion of Entra ID sign-in logs, audit logs, risky user detections, and conditional access events.
• UEBA Entity Pages: Rich entity pages for users and hosts showing risk scores, activity timelines, and related alerts.
• Fusion Detection: Correlates alerts across multiple Microsoft security products to identify multi-stage attacks.
• Identity-Specific Workbooks: Pre-built dashboards for monitoring sign-in anomalies, privilege changes, and application access patterns.
• Hunting Queries: Library of KQL (Kusto Query Language) hunting queries for proactive identity threat hunting.
• Logic Apps Integration: Automated response through Azure Logic Apps — disable accounts, revoke tokens, notify SOC, create tickets.

Pricing

Sentinel pricing is based on data ingestion volume. Pay-as-you-go is $2.46 per GB ingested. Commitment tiers provide discounts: 100 GB/day at $1.96/GB, 500 GB/day at $1.56/GB. Microsoft 365 E5 customers get a significant credit toward Sentinel ingestion for Microsoft data sources.

Pros

• Deepest integration with Microsoft identity stack (Entra ID, Defender, M365)
• Fusion detection provides multi-stage attack correlation across Microsoft security products
• Generous ingestion credits for Microsoft 365 E5 customers
• KQL hunting queries enable sophisticated proactive threat hunting

Cons

• Identity analytics depth depends heavily on Microsoft data sources — less effective in non-Microsoft environments
• UEBA capabilities are less mature than dedicated platforms like Gurucul or Securonix
• KQL learning curve is significant for analysts unfamiliar with the language
• Pricing can be unpredictable as data volumes grow

6. Splunk UBA (User Behavior Analytics)

Best For: Organizations with existing Splunk deployments that want to add identity-centric behavioral analytics to their Splunk SIEM investment.

Overview

Splunk UBA (User Behavior Analytics) adds machine learning-based behavioral analytics to the Splunk platform, extending Splunk Enterprise Security's rule-based detection with identity-centric anomaly detection. UBA processes identity and access data from Splunk indexes, applying unsupervised machine learning to detect behavioral anomalies that predefined rules miss.

Splunk UBA's value proposition centers on augmenting an existing Splunk investment. Organizations already ingesting identity data into Splunk (Active Directory logs, VPN events, cloud access logs) can deploy UBA to extract behavioral insights from that data without duplicating collection or storage.

Key Features

• Unsupervised ML: Machine learning models that automatically detect anomalies without requiring labeled training data.
• Threat Modeling: Pre-built models for account compromise, insider threat, lateral movement, data exfiltration, and privilege abuse.
• Splunk ES Integration: UBA findings feed directly into Splunk Enterprise Security as notable events, enriching the existing SOC workflow.
• Threat Topologies: Visual representation of relationships between users, devices, and resources involved in a threat chain.
• Anomaly Scores: Continuously computed anomaly scores for every user and entity, aggregated into daily risk summaries.
• Custom Models: Support for custom machine learning models alongside pre-built threat models.

Pricing

Splunk UBA is licensed as an add-on to Splunk Enterprise Security, typically priced per user monitored. Pricing varies based on the number of identities and data volume, generally starting at $10-20 per user per month. Splunk Cloud customers may have bundled UBA pricing available.

Pros

• Seamless integration with existing Splunk Enterprise Security deployments
• Leverages data already ingested into Splunk without additional collection
• Threat topologies provide excellent visualization for investigation
• Unsupervised ML reduces the need for manually tuned detection rules

Cons

• Requires existing Splunk Enterprise Security investment
• UBA is a separate deployment from Splunk (runs on its own infrastructure)
• Model tuning and false positive management require ongoing attention
• Splunk pricing model overall can make the total cost substantial

Comparison Matrix

| Feature | Gurucul | Securonix | Exabeam | LogRhythm | Sentinel | Splunk UBA | |---|---|---|---|---|---|---| | Primary Focus | Identity Analytics | Cloud SIEM + UEBA | AI-Driven SIEM | On-Prem SIEM + UEBA | Cloud SIEM | UEBA Add-on | | ML Model Count | 2,500+ | 200+ | 100+ | 50+ | 50+ | 50+ | | Peer Group Analysis | Advanced | Advanced | Moderate | Basic | Basic | Moderate | | Smart Timelines | Yes | Limited | Best-in-class | Limited | Entity Pages | Threat Topologies | | Deployment | Cloud + On-Prem | Cloud (Snowflake) | Cloud | On-Prem + Cloud | Cloud (Azure) | On-Prem + Cloud | | Automated Response | Via SOAR | Built-in | Built-in SOAR | SmartResponse | Logic Apps | Via Splunk SOAR | | Access Analytics | Yes (entitlements) | No | No | No | Limited | No | | Microsoft Integration | Moderate | Moderate | Moderate | Moderate | Native (deep) | Via add-on | | Starting Price | ~$50K/yr | ~$50/GB/day | ~$15/user/mo | ~$25K perpetual | $2.46/GB | ~$10/user/mo addon |

How to Choose the Right Identity Analytics Platform

If identity analytics is your primary need and you want the deepest purpose-built capability, Gurucul's 2,500+ ML models and access outlier detection make it the most comprehensive identity-focused option.

If you are replacing or selecting a SIEM and want integrated UEBA, Securonix and Exabeam both provide strong combined platforms. Choose Securonix for cloud-native scalability and threat chains, or Exabeam for Smart Timelines and per-user pricing predictability.

If you need on-premises deployment for data residency or regulatory reasons, LogRhythm provides a capable SIEM with integrated UEBA that runs entirely in your data center.

If you are a Microsoft shop, Sentinel's native Entra ID integration and fusion detection provide identity analytics depth that no third-party platform can match for Microsoft identity data.

If you already run Splunk, UBA is the most efficient path to identity analytics — it leverages your existing data investment and integrates into your existing SOC workflows.

Conclusion

Identity analytics bridges the gap between IAM and security operations, detecting the identity-based threats that traditional perimeter controls miss. The six platforms reviewed here approach identity analytics from different angles — purpose-built analytics, integrated SIEM+UEBA, and add-on modules — reflecting the diverse needs of security organizations.

For most enterprises, the choice starts with what you already have. Organizations with existing SIEM investments should evaluate the UEBA capabilities of their current platform before adding a separate tool. Organizations building new security analytics capabilities should consider whether they need a full SIEM or can focus specifically on identity analytics.

Regardless of platform choice, the most impactful first step is ensuring that identity data — authentication logs, privilege usage, access request events, and directory changes — is being collected and correlated. The platform is only as good as the data it analyzes.

Frequently Asked Questions

What is the difference between UEBA and identity analytics? UEBA (User and Entity Behavior Analytics) is a broader category that applies behavioral analysis to all users and entities (servers, applications, network devices). Identity analytics specifically focuses on identity-related behaviors — authentication, access, privilege usage, and entitlements. Identity analytics platforms often include UEBA capabilities but narrow the focus to identity-centric threats.

How long does it take for behavioral baselines to become accurate? Most platforms require 2-4 weeks of data collection to establish initial behavioral baselines. Accuracy improves over 60-90 days as models observe more behavioral variation (weekday vs. weekend patterns, monthly cycles, seasonal changes). During the baseline period, expect higher false positive rates.

Can identity analytics detect compromised service accounts? Yes, and this is one of the most valuable use cases. Service accounts have highly predictable behavior patterns — they access the same systems, at the same times, from the same sources. Any deviation (new destination, unusual time, different source IP) is a strong indicator of compromise. Most platforms model service account behavior separately from human user behavior.

Does identity analytics replace SIEM? Not entirely. Identity analytics focuses on identity-based threats, while SIEM covers the broader threat landscape including network attacks, malware, and infrastructure vulnerabilities. Many organizations deploy identity analytics as a module within their SIEM or as a complementary platform that feeds high-fidelity identity alerts into the SIEM for unified SOC operations.

What data sources are most important for identity analytics? The most valuable data sources are: (1) authentication logs from identity providers (Entra ID, Okta, Active Directory), (2) access logs from critical applications and databases, (3) privilege escalation and change events, (4) VPN and remote access logs, and (5) HR data (role changes, terminations) for context. Start with authentication logs and expand from there.