User Entity and Behavioral Analytics

In 2015, Gartner defined the User Entity and Behavioral Analytics (UEBA) category of security technologies. UEBA has gone on to become a critical element of the modern security tech stack, providing organizations with the ability to detect unknown threats and insider attacks.

Before UEBA, security teams used User Behavior Analytics (UBA) to identify suspicious behavior. This technique had its limitations, though. It only observed the actions of human users, making it ineffective against a broad range of persistent, automated, and application-level threats.

By adding “Entity” analytics, cybersecurity vendors opened up the entire network to behavioral analytics fueled by machine learning and AI-powered algorithms. This allows security teams to observe suspicious activity originating from human users as well as network assets, applications, and devices.

What is UEBA and how does it work?

User Entity and Behavioral Analytics is a security technology that detects unusual behavior coming from users, servers, applications, and other network assets. It uses machine learning algorithms to recognize and report on suspicious activity for every single user and entity in the organization’s IT environment.

UEBA platforms work by observing regular network traffic patterns and asset usage and using that data to build a baseline model. When users, applications, or assets deviate from that baseline, the UEBA system triggers alerts, prompting an investigation.

The important distinction between UEBA and other technologies is that it analyzes the entire scope of security risks associated with individual users and entities. Exabeam expresses this risk using a dynamic risk score that instantly informs analysts how severe the risk is.

Here’s an example scenario of UEBA in action:

Consider an employee user account in the organization’s finance department. This account regularly connects to finance-related tools and web applications, and frequently downloads invoices from third-party vendors.

Here’s a short list of activities that might trigger a UEBA alert in this scenario:

• Downloading unusually large files.
• Downloading files from unusual servers or assets.
• Logging into web applications from an unusual device or location.
• Failing to log into web applications too many times.
• Sending an unusual volume of requests to an internal server or asset.
• Receiving an unusual volume of requests from an internal server or asset.
• Attempting to access a sensitive network asset or segment that has never been accessed before.

On their own, any of these activities might simply be a false positive. When added together, obvious risks to operational security begin to emerge. UEBA technology allows analysts to qualify these risks and enhance their investigation with contextually relevant data.

What kinds of threats does UEBA detect?

UEBA platforms address a wide range of security incidents, but they are especially well-suited to detecting threats that other security tools often miss. Here are some examples of the types of threats UEBA-enhanced security tools are often deployed to address:

• Malicious insiders. When rogue employees or supply chain vendors launch attacks from within, they can often bypass or disable static rules-based security tools. Hiding their activity from behavioral analysis is much more difficult to pull off.
• Credential-based attacks. If attackers compromise a privileged user account, they may gain access to every sensitive asset that account has permission to access. UEBA technology can trigger alerts when authorized users and assets begin behaving in suspicious ways.
• Advanced persistent threats. Highly skilled attackers may be able to cover their tracks when conducting long-term reconnaissance, but they can’t hide their behavior from UEBA analytics.
• Data exfiltration. If threat actors attempt to steal large volumes of data from a protected network, they will almost certainly trigger behavioral alerts in a UEBA environment.
• Brute-force attacks. If hackers attempt to target cloud-based assets or third-party authentication systems with brute force attacks, UEBA-enhanced tools may provide early warning that gives your security team a competitive advantage.
• Distributed Denial of Service (DDoS) attacks. UEBA can reliably detect unusual traffic patterns that indicate network assets and devices are being targeted by — or leveraged towards — DDoS attacks.

4 Benefits of implementing UEBA Technology

Many security leaders choose to implement UEBA technology so they can improve operational security performance in four key areas:

1. Better contextualization of security incidents. Providing analysts with a clear framework for identifying and managing risks gives them valuable context and insight into security events in real-time.
2. Improved analyst performance and efficiency. UEBA-enhanced investigations provide highly automated insights and capabilities to analysts. This enables them to respond to security events faster and more accurately then they could with traditional SIEM 1.0 technology.
3. Advanced Zero Trust implementation. By verifying authenticated users for signs of malicious activity, UEBA enhances the organization’s Zero Trust capabilities significantly. It provides unlimited visibility into every user, device, and asset on the network without extending trust to them.
4. Optimal risk management. UEBA lowers the risks associated with complex cyberattacks. It enables faster detection and more comprehensive response while enabling organizations to meet stringent regulatory compliance guidelines and reduce business risk.

UEBA in the SOC Visibility Triad

Since technology vendors like Exabeam introduced UEBA technology to the security community, it has become an integral part of operational security excellence. This has had a profound impact on best-in-class detection and response models like the SOC Visibility Triad.

UEBA technology has fundamentally transformed the way each pillar of the triad functions, and the expectations that security teams can have of their tech stack:

• Security Information and Event Management (SIEM). UEBA enhances SIEM performance so dramatically that it is now the distinguishing feature between SIEM 1.0 and SIEM 2.0 capabilities. For many security leaders, having a modern SIEM means having UEBA.
• Network Detection and Response (NDR). UEBA complements the network traffic insights generated by NDR solutions, bringing context and visibility into local events on monitored devices. This lets analysts bridge the gap between network-level events and local ones.
• Extended Detection and Response (XDR). UEBA enhances endpoint security and allows analysts to take a risk-based approach to correlating endpoint activity with third-party data. This fundamentally transforms the value of endpoint detection and response, enabling full XDR adoption.

Challenges to successful UEBA implementation

UEBA implementation can have a significant impact on your organization’s security posture, but it does come with challenges. Some of the obstacles that security leaders often face when considering UEBA technology include:

• High implementation costs. Many UEBA technology licenses come with a high price tag. Additional costs may arise when security teams need additional configuration expertise and storage space for the large volume of log data that requires analysis.
• Extended deployment time. To produce meaningful results, your UEBA solution must connect to every user and asset in your IT environment. It must then collect data on how these assets interact with one another, which takes time and generates a large volume of data.
• Complex configuration requirements. Generic off-the-shelf detection rules may not produce the results you expect from your UEBA solution. Best-in-class implementations rely on custom detection algorithms designed for the organization’s unique security risk profile.