Imagine being able to halt cybercriminals before they strike. This is the power of UEBA (User and Entity Behavior Analytics). UEBA stands out for its capability to identify suspicious activities that could indicate a security breach or insider threat. It does this by analyzing patterns and behaviors, making it a unique and powerful tool in the cybersecurity landscape.
This article explores 17 powerful use cases demonstrating why UEBA protects your business.
17 Use Cases for UEBA
From catching malicious insiders to spotting compromised accounts, UEBA provides invaluable visibility into your network’s activities. Below, we’ll go through the most critical use cases for UEBA:
1. Detecting Lateral Attacks
Lateral attacks occur when an attacker gains access to a company’s network and moves laterally across different systems to expand their access and increase privileges. These attacks are hazardous because they can go undetected for extended periods, allowing the attacker to remain unnoticed while carrying out malicious threat actor activities like privilege abuse.
UEBA tools are well-suited for detecting lateral attacks because they monitor and analyze user and entity behavior analytics patterns across the entire network.
Through usual behavior baselines, UEBA solutions can find anomalies that may show an attacker moving laterally. For example, if a user account suddenly starts accessing systems or data it typically doesn’t interact with, it could be one of the signs of a lateral attack.
2. Detect Trojan Accounts
UEBA establishes detailed profiles of users’ interactions with your systems and data based on their roles, responsibilities, and historical patterns. So, when a legitimate account becomes an attacker-controlled Trojan, the behaviors that the account exhibits are likely to deviate significantly from the established norms.
The tool can detect these subtle signs like accessing untypical applications, downloading unusual volumes of data, working outside regular hours, or failing to follow business process workflows.
3. Monitor for Account Sharing Policy Breaches
Many organizations have strict policies that forbid sharing user accounts to maintain accountability and prevent unauthorized access. However, enforcing these policies can be challenging, especially in large environments with numerous users and systems.
A primary indicator of account sharing that UEBA can detect includes simultaneous or near-simultaneous logins from geographically different locations, which is highly unlikely to occur under everyday individual use. Another indicator could be varying patterns of activity that are not in line with the established behavior profile of that particular account.
4. Predict Hardware & Software Failures
For hardware components like servers, storage devices, or network equipment, UEBA can monitor resource usage metrics like CPU, memory, or network traffic. If it detects unusual spikes or deviations from routine operational procedures, it could indicate hardware failure.
Similarly, UEBA can analyze application logs, error rates, and transaction response times for software applications. If it notices an increase in error messages, slower response times, or other unusual patterns that have previously led to software crashes o, it could be an early warning sign of potential issues.
5. Data Exfiltration
Data exfiltration can be highly subtle and sophisticated, posing a challenge for traditional security incident measures. However, with its intelligent learning capabilities, UEBA can detect these threats. It first learns what normal data access behavior is for each user, creating a baseline profile. This helps it spot suspicious behavior and abnormal activity, instilling confidence in its ability to protect your data.
With that data, it can spot activities that deviate from this normal baseline. For example, if a user starts transferring files to an unusual external destination like a personal email or cloud storage, UEBA would flag this as suspicious activity related to data exfiltration.
6. DLP and IP Protection
While traditional DLP solutions focus on content inspection and policy enforcement, UEBA complements these efforts by providing behavioral context and user-centric insights.
It monitors user actions across various data sources like email, cloud apps, file transfers, and endpoint activities. It detects unusual behavior that could indicate potential issues like data leakage or mishandling of sensitive information.
7. Account Compromise
UEBA identifies unusual behaviors that suggest an account may have been taken over. This includes anomalies like login attempts at odd hours, access from new locations, or untypical requests for sensitive data. Because it already has a normal behavior baseline for each role and user, the tool can quickly and easily spot any alarming anomalies that suggest account compromise.
8. Privileged Access Abuse Prevention
Privileged accounts, such as those belonging to administrators or power users, have high access permissions within an organization’s IT systems. If these accounts are compromised, it can lead to severe issues like data breaches or system tampering.
UEBA helps mitigate this risk by continuously monitoring privileged user behavior patterns. If a privileged user suddenly accesses sensitive data or systems outside their typical scope or during unusual hours, UEBA can detect this as abnormal behavior and notify the security team.
9. 3rd Partner and Supply Chain Threat Monitoring
Organizations may grant third-party vendors, suppliers, or partners access to their systems as part of their operational processes. However, this exposure increases the risk of external cyber threats, whether intentionally or unintentionally.
UEBA monitors and analyzes these third-party users’ activities and interactions with the organization’s resources and looks for potential threats within the supply chain. These include unauthorized access attempts, data exfiltration, or other suspicious activities.
10. Hijacking and Sharing Detection
It’s not uncommon for users to share files and data, but unauthorized sharing poses a significant threat to data security. UEBA systems help by analyzing user login patterns, geographical IP addresses, and device usage to detect anomalies that could suggest account hijacking.
For instance, if a user’s legitimate credentials are used to log in simultaneously from different geographical locations, UEBA flags this as suspicious and alerts your security team for potential hijacking or unauthorized credential sharing.
11. Insider Risk and Threat Monitoring
UEBA collects and analyzes how users typically interact with your IT systems and then uses that information to establish a baseline of normal activities. Any deviation from typical employee behavior (e.g., strange working hours) is flagged for further investigation, which helps detect insider threats.
With a comprehensive overview of user behavior analytics, UEBA helps security teams proactively identify and mitigate insider risks resulting from malicious intent or negligent actions.
12. Anomalous Activity Monitoring
UEBA uses machine learning, artificial intelligence, and statistical models to analyze large amounts of data and notice deviations from standard patterns. This is vital for catching security threats that might otherwise be missed.
For example, UEBA can spot unusual behaviors, such as a user logging in from a new location at strange times or making uncommon network requests. These could be harmless but also signs of a compromised account or an external threat.
13. Host / Device Compromise Detection
Host or device compromises typically manifest through anomalies in system behavior – such as unexpected software program installations, unusual outbound network traffic, or modification of system files.
UEBA monitors and compares these current device activities against a historical baseline of expected behavior for each device or system type. It can even correlate separate data points that might appear normal in isolation and recognize sophisticated advanced threats, such as APTs (Advanced Persistent Threats) or ransomware.
14. Automate Risk Management
Companies can use UEBA to automate the scoring risk levels associated with different user behaviors, which helps you identify false alarms and which incidents require immediate attention.
For example, UEBA tools can automatically flag behaviors such as multiple failed login attempts as high-risk. This automated threat detection allows security teams to focus their efforts where they are most needed and respond more quickly than traditional risk management approaches that often rely on manual review and intervention.
15. Reconnaissance Monitoring
Reconnaissance activities may involve looking for open ports, mapping out network resources, or quietly checking normal user behaviors and permissions. These ongoing activities can be spread out and hard to detect.
UEBA tools can help by detecting subtle signs of this exploratory behavior in real-time, such as unusual volumes of queries to DNS servers, rapid connections to multiple hosts within a short timeframe, or suspicious access attempts to restricted areas of the network.
16. Security Misconfiguration Identification
Misconfigurations can occur due to a wide range of issues, including improper security settings, default user credentials left unchanged, or unauthorized changes to system configurations.
UEBA tools monitor system configurations and user activities to detect deviations from predefined security policies and baseline configurations.
For example, if a user unexpectedly changes firewall settings or disables the antivirus software program, UEBA systems can quickly alert the security team to these potential vulnerabilities.
17. Speed Up Cybersecurity Investigations
UEBA speeds up cybersecurity risk investigations by giving security teams detailed user and network behavior insights. Rather than manually combing through huge amounts of data to understand what happened during an incident, UEBA tools automatically combine and analyze important data like user logins, file access privileges, network traffic, and application usage. This helps investigators quickly spot suspicious activities, track the extent of an incident, and assess potential damage.
FAQs
What is a UEBA system used for?
A UEBA system detects and responds to cybersecurity threats by analyzing user and network behavior. It helps identify unusual activities, misconfigurations, and potential vulnerabilities, allowing security teams to take timely action to protect their systems.
What are the use cases for user and entity behavior analytics?
UEBA use cases include detecting and responding to cybersecurity threats, identifying unusual activities, misconfigurations, and potential vulnerabilities, and providing detailed insights into user and network behavior to speed up cybersecurity investigations.
Why do we need UEBA?
UEBA is needed to enhance cybersecurity by detecting and responding to potential threats, identifying unusual activities and misconfigurations, and providing detailed insights into user and network behavior. This proactive approach allows security teams to take timely action to protect their systems, ensuring their network’s safety and integrity.
What would be a normal use case of using user behavior analytics?
A typical use case of user behavior analytics (UEBA) is detecting and responding to cybersecurity threats by analyzing user and network behavior. UEBA tools help identify unusual activities, misconfigurations, and potential vulnerabilities, allowing timely action to protect systems.
Conclusion
As we’ve seen throughout these different use cases, UEBA tools are essential for businesses looking to solidify their cybersecurity defense and understand complex user activities.
This technology simplifies monitoring user and entity behaviors, effectively making cybersecurity proactive rather than reactive—and that’s why it’s such an indispensable tool in modern organizations.
