Best 11 User and Entity Behavior Analytics (UEBA) Solutions For Enterprise (2026)
We reviewed the leading UEBA platforms on behavioral baseline sophistication, anomaly detection accuracy, and how well each integrates with SIEM and identity platforms to enrich investigation workflows.
Written by
Caitlin Harris
Technical Review by
Laura Iannini
Quick Summary
User and Entity Behavior Analytics (UEBA) solutions establish behavioral baselines and flag deviations that indicate insider threats or compromised accounts — catching the threats that look like legitimate activity until the behavior pattern changes. Rule-based tools cannot fill the behavioral detection gap that UEBA addresses. We reviewed the top platforms and found Teramind, ManageEngine Log360, and ActivTrak to be the strongest on baseline model sophistication and anomaly detection accuracy.
Detecting insider threats and anomalous user behavior is harder than it should be. Your security team drowns in alerts, most of which turn out to be false positives. Meanwhile, the one threat that matters slips through because it looked like normal activity to legacy rule-based systems.
User and entity behavior analytics platforms claim to solve this by learning what normal looks like and flagging real deviations. The problem is that claimed capability doesn’t always match operational reality. Some platforms require months of tuning before delivering value. Others scale from endpoint monitoring but miss critical cloud activity. A few pack so much complexity into their interfaces that your team struggles just to get through initial setup.
We evaluated 11 UEBA solutions across insider threat detection, behavioral analytics, cloud visibility, and integration depth with existing SIEM infrastructure. We evaluated each for detection accuracy, deployment friction, false positive rates, and how well they handle mixed on-premises and cloud environments. We also reviewed customer feedback to see where vendor promises diverge from field experience.
This guide gives you the testing insights and decision framework to select a UEBA solution that catches real threats without creating an alert fatigue nightmare for your team.
Our Recommendations
We evaluated each solution’s strengths and trade-offs across User And Entity Behavior Analytics (UEBA) Solutions. Here’s how to pick the right fit:
- Best For Real-Time Monitoring That Actually Works: Teramind live desktop streaming and incident video playback provide concrete investigation evidence.
- Best For ML-Powered Detection Meets Log Consolidation: ManageEngine Log360 unified dashboard consolidates logs from cloud, on-premises, and hybrid sources effectively.
- Best For Productivity Intelligence Over Pure Security: ActivTrak accurate active time tracking provides reliable productivity metrics per user.
- Best For Behavioral Baselines With Context: Cynet UBA offers behavioral baselines auto-generate from role, location, and schedule data.
- Best For Risk Profiling From Data You Already Have: IBM Security QRadar SIEM UBA uses existing qradar event data without requiring separate collection infrastructure.
Teramind is a user behavior monitoring platform that helps prevent insider data loss and detect insider threats. The platform provides real-time activity monitoring across all endpoint devices, with support for Windows and macOS. Deployment options include Oracle, AWS, and Azure, with on-premises support for air-gapped networks.
Teramind Key Features
Teramind enables admins to monitor and control user actions directly on the device, with real-time data inspection and intervention to prevent malicious file uploads or browsing activities. The platform can also track tools used to obfuscate employee activities, such as mouse jigglers. Admins configure customizable rules to detect and prevent harmful user activity based on web browsing, file actions, and more. Automated responses include admin alerts and device lockouts when specific workflows are triggered.
The admin console provides live streaming of all desktop activity, video playbacks of suspicious incidents, and comprehensive reports on risky behaviors and productivity levels. Teramind includes granular DLP controls that inspect all email contents, attachments, and network data. The platform automatically prevents data transfers that breach corporate policies and recognizes financial information, PII, and other sensitive data types.
Our Take
We think Teramind is a strong option for organizations that need combined user behavior monitoring and data loss prevention. The real-time intervention capabilities and comprehensive activity reporting stand out, and the air-gapped deployment option is good to see for high-security environments.
Strengths
- Real-time activity monitoring with live desktop streaming and video playback
- Customizable rules engine with automated lockout and alerting responses
- Granular DLP controls inspect email, attachments, and network data in real time
- Supports air-gapped on-premises deployment for high-security environments
- Recognizes and protects financial information, PII, and sensitive data types automatically
Cautions
- Pricing not publicly available; requires contacting sales for a quote
ManageEngine Log360 is a unified SIEM platform combining log management, DLP, and CASB capabilities for hybrid environments. We think it’s best understood as a mid-market SIEM with UEBA layered on top, rather than a dedicated behavior analytics tool. For teams that need threat detection and compliance monitoring without enterprise-tier pricing, it’s a strong option to consider.
ManageEngine Log360 Key Features
The unified dashboard is the core strength. It consolidates logs from cloud, on-prem, and hybrid sources into a single console, and the event correlation across environments is effective. The UEBA add-on flags behavioral anomalies like unusual logon patterns, file deletions from unexpected hosts, and repeated authentication failures. Risk scoring prioritizes threats so analysts focus on real incidents first rather than chasing noise.
What Customers Say
Customers who get past initial setup praise the unified dashboard and time savings from automation. Log consolidation simplifies day-to-day monitoring, and teams report faster detection and resolution of security issues. Something to be aware of is that some organizations struggled with integration complexity.
Our Take
We think Log360 delivers strong value if your team can invest time in proper configuration. The feature set competes well above its price point once running. If you need a SIEM that works immediately out of the box, plan for a longer runway here.
Strengths
- Unified dashboard consolidates logs from cloud, on-prem, and hybrid sources
- Risk scoring prioritizes threats so analysts focus on real incidents
- UEBA add-on catches anomalies that rule-based detection misses
- Competitive pricing compared to enterprise SIEM alternatives
Cautions
- Reviews note integration can be complex
ActivTrak
ActivTrak is a cloud-based user behavior analytics platform focused on productivity tracking and anomaly detection rather than deep security investigations. We think it fits best for organizations wanting workforce visibility without heavy security infrastructure, particularly hybrid and remote teams. It now has over one million users.
ActivTrak Key Features
The productivity intelligence is the differentiator. Activity logs, screenshots, and video reports give admins visibility into user patterns, and customizable dashboards surface behavioral data immediately after deployment. Location tracking helps inform hybrid work policies, and personalized reports can be shared directly with employees. Automatic responses trigger when activities deviate from baselines. ActivTrak has also introduced AI-powered features including an AI Advisor for natural language workforce queries and AI adoption analytics to measure how teams interact with AI tools.
What Customers Say
Customers consistently praise the accuracy of active time tracking per user. Workload distribution insights help teams make better operational decisions. With that said, some customers flag the snapshot feature as too restrictive for detailed security investigations. Contract auto-renewal policies also draw criticism for making cancellation unnecessarily difficult.
Our Take
We think ActivTrak works best when productivity optimization matters as much as security monitoring. If you need deep forensic capabilities for insider threat investigations, there are stronger options in the dedicated UEBA space. For workforce analytics with behavioral baselines, it delivers solid value.
Strengths
- Accurate active time tracking with reliable per-user productivity metrics
- Dashboards surface behavioral insights immediately after deployment
- Location analytics support hybrid work policy decisions
- AI Advisor provides natural language workforce queries
Cautions
- Users note snapshots lack depth for serious security investigations
- Reviews flag contract auto-renewal makes cancellation difficult
Cynet UBA
Cynet delivers user behavior analytics as part of its broader XDR platform, targeting organizations that want insider threat detection bundled with endpoint protection. We think it makes sense for teams preferring consolidated security tools over point solutions, particularly mid-market organizations with lean security staff.
Cynet UBA Key Features
The behavioral baselining is the core strength. Cynet builds user profiles using role, group, geolocation, and working hours to define normal patterns, then flags deviations like first-time logins, off-hour access, and new VPN connections without manual rule creation. The platform correlates user activity with endpoint events, file access, and network destinations, which helps distinguish actual threats from noise. Automated remediation can disable compromised accounts immediately or queue incidents for analyst review.
What Customers Say
Customers consistently highlight the support team as a differentiator. Account managers stay accessible and push cases through when needed. One organization renewed for five additional years after four years of use, citing product reliability and budget fit. Something to be aware of is that false positive tuning requires ongoing attention after initial deployment, and some users feel third-party integrations fall short of expectations.
Our Take
We think Cynet UBA makes sense if you already use or plan to adopt their XDR platform. For mid-market teams wanting behavioral analytics without adding another vendor relationship, this approach delivers practical value. Setup and onboarding get positive marks for being straightforward.
Strengths
- Behavioral baselines auto-generate from role, location, and schedule data
- Correlates user events to endpoints and network context automatically
- Support team responsiveness earns consistent praise
- Consolidated platform reduces vendor sprawl for lean security teams
Cautions
- Customers note false positive tuning needs ongoing attention
- Reviews mention third-party integrations fall short of expectations
IBM Security QRadar SIEM UBA
IBM QRadar SIEM UBA adds behavioral analytics to the established QRadar platform, targeting enterprise security teams already invested in the IBM ecosystem. It builds user risk profiles from existing event and flow data rather than requiring separate data collection. It’s worth noting that Palo Alto Networks acquired IBM’s QRadar SaaS assets in 2024, and the QRadar SaaS products have reached end of life; on-prem QRadar SIEM with the UBA app remains available.
IBM Security QRadar SIEM UBA Key Features
The key advantage is that QRadar UBA uses existing log ingestion to generate behavioral insights, avoiding duplicate data pipelines. Risk profiling assigns severity scores based on event patterns, and unified user identities consolidate multiple accounts belonging to the same person, eliminating blind spots from fragmented identity data. The user import wizard pulls from LDAP, Active Directory, reference tables, and CSV files. Machine learning add-ons extend detection beyond rule-based approaches.
What Customers Say
Customers describe QRadar as powerful for correlating massive event volumes in real time. Deep visibility into network activity and wide log source support earn consistent praise. With that said, the interface feels dated and navigation frustrates even experienced analysts. Complexity demands significant time investment before delivering value, and formal training is typically required for new team members.
Our Take
We think QRadar UBA fits organizations with dedicated security operations staff who can invest in mastering the platform. The capability ceiling is high, but you need resources to reach it. Given the Palo Alto acquisition of QRadar’s SaaS assets, we’d recommend clarifying the product roadmap with IBM before committing to new deployments.
Strengths
- Uses existing QRadar event data without separate collection infrastructure
- Unified identity consolidation eliminates fragmented account blind spots
- Broad log source integrations work effectively out of the box
- ML add-on extends detection beyond static rule-based approaches
Cautions
- Reviews flag the interface as dated with confusing navigation
- Users report a steep learning curve requiring formal training
Logpoint Converged SIEM UEBA
Logpoint bundles SIEM, SOAR, UEBA, and EDR into a single platform with a unified taxonomy. We think it’s a strong option for SOC teams and MSSPs who want consolidated security operations without stitching together multiple point solutions. The single-taxonomy approach is the differentiator here.
Logpoint Converged SIEM UEBA Key Features
The unified taxonomy standardizes logs across cloud and on-prem systems automatically, which makes cross-environment investigations feel more natural. Machine learning establishes behavioral baselines for users, peer groups, and network entities without manual rule creation. Risk scoring prioritizes high-fidelity incidents so analysts focus on real threats. The platform emphasizes collecting meaningful data over raw volume, which helps teams extract insights without drowning in noise.
What Customers Say
Customers praise how the platform transforms security data analysis from overwhelming to manageable. Integration with existing security, identity, and infrastructure tools works smoothly. Something to be aware of is that the structured methodology creates a real learning curve. Mastering the taxonomy and query language takes dedicated time. Customers also note performance slowdowns with large datasets.
Our Take
We think Logpoint fits teams willing to invest in learning its structured approach. For organizations prioritizing data sovereignty or wanting SIEM and SOAR unified natively, this delivers solid value once your team reaches proficiency. If you need a platform that works immediately without training, expect friction.
Strengths
- Single taxonomy standardizes logs for faster cross-platform investigations
- Bundles SIEM, SOAR, UEBA, and EDR without separate integrations
- Risk scoring surfaces high-priority incidents and reduces alert fatigue
- Minimal infrastructure changes required for deployment
Cautions
- Customers note the taxonomy and query language demand significant learning
- Reviews mention performance degrades with very large datasets
LogRhythm UEBA
LogRhythm UEBA is a cloud-native add-on that extends the LogRhythm SIEM platform with machine learning-driven anomaly detection. It targets existing LogRhythm customers who need deeper user behavior analytics without deploying a separate tool. It’s worth noting that LogRhythm completed a merger with Exabeam in July 2024, and the unified company now operates under the Exabeam brand. LogRhythm Cloud customers were scheduled to migrate to the Exabeam Security Operations Platform by March 2025, while self-managed LogRhythm SIEM continues with ongoing updates.
LogRhythm UEBA Key Features
The plug-and-play implementation minimizes setup friction for teams already running LogRhythm SIEM. The system continuously adapts to your specific environment rather than relying solely on static rules. The Machine Data Intelligence Fabric enriches and normalizes data before feeding it into both the SIEM and UEBA components. Correlation capabilities pull logs from multiple sources and surface insights across use cases effectively.
What Customers Say
Customers praise the correlation engine and intuitive interface for interpreting threat data. Dashboard creation and report generation feel straightforward. With that said, experiences diverge sharply on usability. Some find basic tasks frustrating with unhelpful error messages. Search performance slows noticeably with large datasets, and limited customization options surface as pain points.
Our Take
We think this add-on makes sense if you already run LogRhythm SIEM and want behavioral analytics without adding another vendor. Given the Exabeam merger, we’d recommend checking the latest product roadmap to understand how LogRhythm UEBA fits into the combined company’s plans before committing to new deployments.
Strengths
- Plug-and-play deployment for existing LogRhythm SIEM customers
- Correlation engine surfaces insights across multiple log sources
- Continuous learning adapts detection to your specific baseline
- File integrity monitoring runs without significant resource overhead
Cautions
- Users report search performance degrades with large datasets
- Reviews note limited customization for advanced use cases
Rapid7 InsightIDR
Rapid7 InsightIDR is a cloud-native SIEM with built-in UEBA and XDR capabilities. We think it fits well for security teams wanting detection and response without heavy infrastructure investment, particularly smaller teams who benefit from managed detection services. SaaS delivery simplifies setup significantly.
Rapid7 InsightIDR Key Features
The machine learning baselines user activity and flags deviations with minimal tuning required. User and asset behavior timelines correlate activities across the network to specific individuals, which makes investigation workflows more intuitive. Out-of-the-box detections work effectively from initial deployment. The platform scales flexibly as organizations shift between on-prem and cloud environments. Recent updates include Microsoft Entra ID as an event source, enabling deeper visibility into identity-based activity.
What Customers Say
Customers highlight smooth initial deployment with hands-on vendor assistance. Agent reliability impresses, collecting data consistently from both on-prem systems and remote workers. The interface makes investigation accessible for analysts at any experience level. Something to be aware of is that new features frequently become separate chargeable products rather than enhancements to existing subscriptions. The proprietary query language also creates friction for experienced analysts.
Our Take
We think InsightIDR delivers best value when paired with Rapid7’s MDR offering, especially for lean security teams. If you have experienced analysts who prefer full control and custom workflows, the feature segmentation and query limitations may frustrate. Budget for feature growth beyond initial licensing costs.
Strengths
- SaaS deployment with hands-on setup assistance accelerates time to value
- Agent reliably captures data from remote and on-prem endpoints
- Alert prioritization reduces false positives for lean teams
- User behavior timelines correlate activity to specific individuals
Cautions
- Customers note new features often split into separate paid products
- Users report the proprietary query language has a learning curve
Securonix UEBA
Securonix UEBA is an enterprise-grade behavior analytics platform built on patented machine learning. We were impressed by the depth of threat detection here. It targets large organizations with complex environments, particularly those needing to layer advanced analytics on top of existing SIEM investments without replacing infrastructure.
Securonix UEBA Key Features
The platform maps threat chains to both MITRE ATT&CK and US-CERT frameworks, giving analysts familiar reference points during investigations. Peer group analysis automates anomaly detection by comparing user behavior against similar roles; this contextual approach surfaces deviations that static rules miss. Cloud visibility is strong, with built-in APIs connecting to major infrastructure and application platforms. The platform also incorporates GenAI-enabled workflows and modular AI agents to assist analysts with investigations and response actions.
What Customers Say
Customers describe strong vendor partnership throughout implementation and ongoing operations. Securonix actively helps configure policies and threat models rather than leaving teams to figure it out alone. Post-deployment support maintains that engagement level. With that said, the enterprise-focused architecture may exceed requirements for smaller security teams, and advanced capabilities require mature security operations to fully use.
Our Take
We think Securonix fits enterprises with mature security operations and existing SIEM infrastructure they want to enhance. If your organization handles sensitive data with significant insider threat exposure, this deserves evaluation. Smaller teams may find the platform more than they need.
Strengths
- Threat chain mapping to MITRE ATT&CK and US-CERT frameworks
- Deploys on top of existing SIEM without infrastructure replacement
- Peer group analysis detects role-specific behavioral anomalies
- Vendor actively supports policy and threat model configuration
Cautions
- Reviews note the architecture may exceed smaller team requirements
- Customers flag advanced features require mature security operations
Splunk User Behavior Analytics
Splunk UBA is a machine learning-powered threat detection layer for organizations already invested in the Splunk ecosystem. It targets security teams drowning in alerts who need automation to surface real threats from massive event volumes. It’s important to note that Splunk UBA reached End of Sale in December 2025 following Cisco’s acquisition of Splunk; UEBA capabilities are now being integrated directly into Splunk Enterprise Security (ES) Editions. Support for existing licenses continues through December 2026.
Splunk User Behavior Analytics Key Features
The platform condenses billions of raw events into a prioritized threat queue without requiring heavy analyst involvement. Machine learning algorithms connect anomalies across users, accounts, devices, and applications to reveal attack patterns. Kill chain visualization shows threats in context rather than as isolated alerts. The user feedback learning feature lets you customize anomaly models based on your specific policies, assets, and user roles, which improves confidence in severity scoring over time.
What Customers Say
Customers highlight ease of investigation once case-specific dashboards are configured. Insider threat detection and abnormal pattern identification get consistent praise. The platform handles enormous data volumes effectively. Something to be aware of is that false positive tuning requires ongoing attention, and initial integration requires significant time investment before delivering value.
Our Take
We think Splunk UBA made sense for organizations already running Splunk SIEM. Given the End of Sale and transition to Splunk Enterprise Security Editions, we’d recommend evaluating the new ES-integrated UEBA capabilities rather than pursuing standalone Splunk UBA. If you’re already licensed, plan for the migration path.
Strengths
- Reduces billions of events to prioritized threats automatically
- Kill chain visualization contextualizes threats for faster decisions
- Custom anomaly models adapt to your policies and user roles
- Detects lateral movement and C2 activity across entities
Cautions
- Reached End of Sale December 2025; migrating to Splunk ES
- Users report false positive tuning demands ongoing attention
Varonis Data Security Platform
Varonis is a data-centric security platform combining UEBA, data classification, and automated remediation. We think it’s one of the strongest options if your security priorities are driven by data protection rather than endpoint threats. It covers multi-cloud, on-prem, and hybrid environments with a focus on sensitive data exposure.
Varonis Data Security Platform Key Features
The predictive threat models analyze user behavior across Windows, NAS, and Microsoft 365 without requiring manual configuration. Detection covers ransomware infections, compromised service accounts, and insider threats. The data-first approach means alerts connect directly to what attackers are targeting. Automated discovery classifies and labels sensitive data continuously, giving you a real-time view of compliance posture and exposure risk rather than point-in-time snapshots.
What Customers Say
Customers consistently highlight the support team as a differentiator. Varonis provides a global Incident Response team that investigates abnormal activity directly, extending your security operations capacity. Access management automation earns specific praise. With that said, some customers note the platform requires significant customization before delivering full value. Organizations with complex data estates should budget for configuration time.
Our Take
We think Varonis fits organizations where data protection drives security priorities. For compliance-driven environments managing regulated data across hybrid infrastructure, this platform addresses the core problem directly. If your primary concern is endpoint threats rather than sensitive file exposure, other tools in this space may align better.
Strengths
- Predictive threat models work without manual rule configuration
- Automated data classification provides continuous exposure visibility
- Global Incident Response team extends investigation capacity
- Access management automation simplifies permission controls
Cautions
- Reviews flag significant customization needed for complex environments
- Customers note the data-centric focus may not suit endpoint-first teams
What To Look For: UEBA Solutions Checklist
When evaluating UEBA solutions, we’ve identified seven essential criteria. Here’s the checklist of questions you should be asking:
- Behavioral Baseline Accuracy: Does the platform automatically establish baselines for users, peer groups, and entities? Can it adjust baselines based on schedule, role, and location without manual rule creation? Does it learn from your specific environment or rely on generic patterns?
- False Positive Management: What’s the false positive rate in field deployments? Can you tune models based on your risk tolerance? Does the platform track which alerts turned out to be legitimate activity so you can improve detection over time?
- Integration With Existing SIEM: Does it integrate with your current SIEM without requiring infrastructure replacement? Can it pull data from your existing log sources? Does it enrich your SIEM with behavioral context, or does it operate as a standalone tool?
- Cloud and SaaS Visibility: Can it detect anomalous behavior in cloud applications and SaaS workloads? Does it correlate on-premises and cloud activity for cross-environment threat detection? How deep is integration with Microsoft 365, Salesforce, and other major platforms?
- Incident Context and Investigation: When the platform flags an anomaly, what context does it provide? Can analysts see user timelines, activity history, and related events without jumping between tools? Does it map detections to MITRE ATT&CK or other threat frameworks?
- Automation and Response: Can you define automated responses to specific threat patterns? Can it trigger account disablement, password resets, or escalation to a SOC team? Does it enable playbook-driven response workflows without manual intervention?
- Deployment and Operational Overhead: How much time does initial deployment take? Does it require extensive tuning before delivering value? Will your team need specialized training, or can analysts with moderate security experience drive the platform?
Weight these criteria based on your environment. Organizations with mature security operations and existing SIEM infrastructure should prioritize integration depth and minimal infrastructure overhead. Teams focusing on insider threat protection should emphasize behavioral accuracy and investigation context. If you’re trying to reduce false positive noise, investigation tuning and user feedback mechanisms matter most.
How We Compared The Best User And Entity Behavior Analytics Solutions
Expert Insights is an independent editorial team that researches, tests, and reviews cybersecurity and IT solutions. No vendor can pay to influence our review of their products. Our Editor’s Scores are based solely on product quality. Before testing, we map the full vendor market for each category, identifying all active vendors from market leaders to emerging challengers.
We evaluated 11 UEBA platforms across behavioral analytics capabilities, insider threat detection, cloud visibility, SIEM integration, and false positive rates. Each platform was tested in controlled environments simulating hybrid infrastructure with both on-premises and cloud workloads. We assessed detection accuracy against known attack patterns, ease of deployment, alongside interface usability and operational overhead required to maintain and tune the platform after initial deployment.
Beyond hands on testing, we conducted in depth market research and reviewed customer feedback to validate vendor claims against operational reality. We spoke with product teams to understand architecture decisions and known limitations. Our editorial and commercial teams operate independently. No vendor can pay to influence our review of their products.
This guide is updated quarterly. For full details on our evaluation process, visit our How We Test & Review Products.
The Bottom Line
No single UEBA solution works for every organization. Your choice depends on whether you need standalone behavioral monitoring, integration with existing SIEM infrastructure, or consolidated security operations.
If insider threat detection with real-time visibility is your priority, Teramind delivers agent-based monitoring with desktop streaming and incident video playback. Accept that the admin interface requires time investment before your team reaches proficiency.
If you already run SIEM and want to layer behavioral analytics on top without wholesale infrastructure replacement, Securonix UEBA provides enterprise-grade detection with peer group analysis and threat chain mapping. The vendor actively supports policy configuration rather than leaving your team to figure it out alone.
If you want SIEM, SOAR, UEBA, and EDR unified under a single taxonomy, Logpoint Converged SIEM transforms how your team investigates across cloud and on-premises systems.
If Splunk anchors your environment, Splunk User Behavior Analytics is the natural choice. Machine learning baselines adapt automatically, and kill chain visualization contextualizes threats without heavy analyst involvement.
If data protection drives your security priorities, Varonis Data Security Platform focuses behavioral analytics on data access patterns. Automated discovery continuously classifies sensitive data, and the global Incident Response team extends your investigation capacity.
For lean security teams wanting cloud-native SaaS without infrastructure overhead, Rapid7 InsightIDR combines SIEM, UEBA, and XDR. The platform works particularly well when paired with Rapid7’s managed detection and response offering.
Read the individual reviews above to dig into deployment specifics, integration depth, false positive rates, and the trade-offs that matter for your environment.
FAQs
Everything You Need To Know About UEBA Solutions (FAQs)
Cybercriminals are continuously finding new ways to evade traditional, perimeter-based security technologies such as firewalls, email gateways, and web gateways. These tools usually identify anomalous behavior using statistical analysis and user-defined correlation rules. While these methods are good at detecting known threats, they struggle to detect unknown or zero-day attacks and insider threats.
That’s where user and entity behavior analytics (UEBA) comes in.
UEBA is a type of cybersecurity solution that uses a combination of machine learning and deep learning algorithms, along with statistical analysis, to identify anomalous behavior amongst the users and entities (e.g., endpoints, routers, servers, hosts, applications, and data repositories) connected to a network. Anomalous behavior could be any instances where a user or entity is acting in deviation of a “normal” baseline, such as someone logging in from an unusual location, requesting access to apps they wouldn’t normally use, or downloading more files than normal, or a server receiving far more requests than usual. This kind of behavior could indicate that an entity or a user’s account has been compromised, so, when the UEBA solution detects it, it alerts the IT or security team so they can investigate the activity and remediate anything malicious. Some UEBA solutions also offer automated remediation actions for certain alerts, such as logging users out of their accounts when suspicious activity is detected.
UEBA is an evolution of earlier “UBA” solutions, which focused solely on user behavior analytics. One of the main drivers of this evolution was the introduction of Internet of Things (IoT) devices to the workplace. IoT devices are notoriously difficult to secure, making them a popular target for cybercriminals, and they generate huge amounts of data. By expanding their analyses across entities other than users, UEBA solutions can detect complex attacks across the entire network—including network components, cloud assets, endpoints, and IoT devices.
Once installed, UEBA solutions collect data from across the network to establish a baseline of normal behavior for all the users and entities on that network. Once the solution has established this baseline, it can start analyzing the data it collects, comparing real-time activity to the baseline to identify any anomalous—and potentially malicious—behavior. UEBA solutions usually allow a certain level of deviation from the baseline, but once that deviation becomes too great, the solution alerts the IT or security team.
For this to work, UEBA tools are made up of three main components:
- A UEBA solution uses data analytics to build a profile of each user and entity’s “normal” behavior. It then continuously monitors user and entity behavior and applies statistical models and machine learning algorithms to identify anomalous activities.
- UEBA tools integrate data from a wide range of sources, including systems logs, packet capture data, and information fed into them from other security tools. This allows the UEBA tool to compare data from each source so it can more accurately detect abnormal activity.
- The UEBA tool presents its findings to the IT or security team. This could involve sending an alert that recommends further investigation, or it could involve the UEBA tool taking automatic action to remediate the threat, such as shutting down a user’s network connectivity.
Traditional, perimeter-based security tools are no longer able to prevent organizations against today’s most sophisticated cyberthreats, such as zero-day attacks and insider threats. Cybercriminals are increasingly finding new ways to evade these technologies, most often using social engineering and account compromise attacks. These kinds of attack can be incredibly difficult to detect, as they don’t involve an attack on a system, but instead directly target users, so the only way to spot them is by closely examining users’ behavior for anything that might suggest they aren’t who they say they are. Additionally, threat actors are increasingly targeting vulnerable BYOS and IoT devices connected to a network—both of which can be difficult to protect using traditional security tools.
To fill this gap in security, two main types of solution have emerged: extended detection and response (XDR), and user and entity behavior analytics.
By focusing on user and entity behaviors, UEBA solutions can detect even the smallest indicators that a user’s account or network component has been compromised. By detecting these types of breaches early, they can help prevent data loss, system corruption, and financial loss.
As well as enabling organizations to detect more sophisticated threats, UEBA tools help reduce the burden on IT and security teams by automating the threat detection process, and facilitating faster incident response. This enables IT and security staff to spend less time trawling through system logs, and focus their energy on actually responding to threats.
This, in turn, leads to the final benefit of implementing a UEBA solution: a reduction in IT spend.
Written By
Caitlin Harris is the Deputy Head of Content at Expert Insights. As an experienced content writer and editor, Caitlin helps cybersecurity leaders to cut through the noise in the cybersecurity space with expert analysis and insightful recommendations.
Prior to Expert Insights, Caitlin worked at QA Ltd, where she produced award-winning technical training materials, and she has also produced journalistic content over the course of her career.
Caitlin has 8 years of experience in the cybersecurity and technology space, helping technical teams, CISOs, and security professionals find clarity on complex, mission critical topics like security awareness training, backup and recovery, and endpoint protection.
Caitlin also hosts the Expert Insights Podcast and co-writes the weekly newsletter, Decrypted.
Technical Review
Laura Iannini is a Cybersecurity Analyst at Expert Insights. With deep cybersecurity knowledge and strong research skills, she leads Expert Insights’ product testing team, conducting thorough tests of product features and in-depth industry analysis to ensure that Expert Insights’ product reviews are definitive and insightful.
Laura also carries out wider analysis of vendor landscapes and industry trends to inform Expert Insights’ enterprise cybersecurity buyers’ guides, covering topics such as security awareness training, cloud backup and recovery, email security, and network monitoring. Prior to working at Expert Insights, Laura worked as a Senior Information Security Engineer at Constant Edge, where she tested cybersecurity solutions, carried out product demos, and provided high-quality ongoing technical support.
Laura holds a Bachelor’s degree in Cybersecurity from the University of West Florida.