User and Entity Behavior Analysis (UEBA) is a security solution that often leverages AI and machine learning algorithms to detect anomalous behavior on networks and computer systems. It analyzes behavioral patterns of users and other entities within corporate networks, servers, routers, and endpoints.
UEBA differs from the more basic User Behavior Analysis (UBA) in that it covers all entities, including devices and applications, not just users. UEBA is thus a more sophisticated form of UBA. It has specialized monitoring for non-human (machine) entities and processes, such as managed and unmanaged endpoints, cloud and mobile applications, and automated malicious processes.
Gartner added the “E” to UEBA in 2017. The objective was to help the security industry improve profiling of non-user entities to enable more accurate threat discovery.
Related content: Read our guide to UEBA Gartner (coming soon)
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UEBA solutions monitor the behavior of all users and entities in an organization’s network. They process the behavioral data to determine if a specific activity or behavioral trend may indicate or enable an attack. UEBA technology can identify what constitutes a normal activity and what might be a threat.
Attackers can infiltrate the network using stolen employee credentials, but the attacker’s malicious activity stands out from normal behavioral patterns, allowing UEBA to detect it as an anomaly.
The data processed by UEBA can come from a data repository (i.e., a data lake) or a SIEM solution that collects data from multiple sources. UEBA integrates varying information types, including packet capture data, logs, and other data from security monitoring platforms. Many organizations combine UEBA with SIEM to aggregate and process data.
The analytics component of UEBA can detect anomalies with various analytic techniques, including rule-based, signature-based, statistical, and machine learning models. In addition to tracking devices and events, UEBA monitors potential insider threats using machine learning. It works by establishing a baseline of normal activity to compare suspicious behavior.
If a user logs in from an unusual location, accesses unusual files or tries to access files too frequently or at unusual times, this might indicate improper use of access privileges. Advanced analytics capabilities should complement the traditional rule-based analytics of a SIEM, allowing UEBA to detect many complex and simple attack types, as opposed to a specialized tool that focuses on monitoring one thing (i.e., employees).
UEBA’s ability to detect anomalous behavior in real time allows it to send alerts immediately. Security analysts can thus respond quickly to threats and prevent serious breaches. Without UEBA, security teams need to filter alerts to identify which indications pose a real risk. UEBA automates this analytical process to prioritize actual threats.
Learn more in our detailed guide to UEBA tools (coming soon)
UEBA solutions and behavior-based security are useful for various scenarios. Several advanced threats can circumvent and evade detection by conventional security tools, but a UEBA system will detect and block them. These include:
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Security Information and Event Management (SIEM) is a comprehensive set of technologies providing an in-depth view of an organization’s security profile. It uses threat data and event information to help security teams identify normal patterns and anomalous events or trends. UEBA uses a similar approach, alerting security teams to anomalies, but it adds user and entity activity to the data mix.
In short, SIEM focuses on security events, and UEBA emphasizes behavioral patterns. Another major difference is that SIEM is a rule-based solution. Attackers can identify and evade SIEM rules to avoid detection. SIEM rules usually aim to identify threats immediately, but advanced attacks may occur over a long period.
On the other hand, UEBA uses sophisticated algorithms and risk scoring instead of rules. These techniques allow UEBA to identify suspicious activity when spread over time. An IT security best practice is to combine UEBA and SIEM to provide well-rounded threat detection.
Learn more in our detailed guide to UEBA and SIEM (coming soon)
UEBA helps strengthen an organization’s security system, covering the blindspots that traditional security solutions cannot, including SIEM, user monitoring, and rule-based access control (RBAC). Implementing UEBA alongside other security tools helps increase their flexibility, minimize false positives, and identify more advanced threats.
Organizations can significantly improve their security posture with the following benefits of a UEBA solution:
The deployment and configuration of UEBA tools can involve several challenges:
After an organization sets up and activates its UEBA system, it can apply several principles to help ensure that the system performs well. The following security best practices apply to various security tools, including UEBA. How an organization uses these systems is an important factor in increasing security by ensuring all employees have the necessary knowledge to implement security.
A major factor in the proper use of UEBA systems is ensuring that employees have the knowledge and skills necessary to operate these systems. Organizations can use a security memo template to help employees understand the importance of security. It is also important to raise security awareness and best practices throughout the year—this applies to UEBA systems and other types of security software.
Business security goals and proper user activity are essential considerations for the baselining period. This period should not be too long or too short—if the baselining period ends too soon, there may not be enough time to collect accurate information, and the false positive rate may increase. On the other hand, if an organization takes a long time to baseline information, some malicious activity could pass as normal behavior.
Because user and entity activity is constantly changing, baseline data may require periodic updates. Employees can switch roles, projects, and privilege levels, enabling them to perform new activities. Organizations can configure their UEBA system to collect data automatically and adjust baselines as changes occur.
This best practice is more specific to UEBA solutions—organizations must consider their overall threat profile when creating rules and policies to identify attacks. One of the main advantages of UEBA is its ability to detect insider threats effectively, just as it detects external threats. However, insider threat detection is only possible if the system is configured to look for them.
To secure their UEBA systems, organizations must give the appropriate personnel the appropriate privileges. Not everyone should have access to the UEBA system. Only specific team members should have permission to view security data, and the system should only notify these individuals.
Many organizations underestimate the threat posed by non-privileged user accounts. Attackers often target low-access accounts and use them to escalate their privileges and hack sensitive systems. A UEBA system helps detect unauthorized attempts to escalate privileges. The software should be configured to alert the security team when privilege escalation incidents occur.
Cynet’s AutoXDR platform includes a User Behavior Analytics component that monitors user behavior to spot and isolate compromised accounts and malicious insiders. It can help identify suspicious activity such as anomalous logins, users accessing sensitive data from unsecured locations or devices, and first time logins to sensitive systems.
Cynet UBA provides the following capabilities: