Preventing insider threats is crucial for every organization, especially as incidents of this kind are increasingly common. Recent reports indicate that the average total cost of insider-related incidents is around $17.4 million.
Here’s the breakdown according to one report:
- 55% of incidents are due to employee negligence
- 20% involve compromised or outsmarted users
- 25% result from malicious insider activity
Moreover, 83% of organizations reported experiencing at least one insider attack in the past year (as of 2024). These statistics highlight the growing importance of implementing strong monitoring, behavior analytics, and awareness programs to detect and mitigate insider risks — as such incidents not only cause operational disruption but also lead to significant financial and reputational loss.
Introduction :
QRadar User Entity Behavior Analytics (UEBA) helps detect insider threats by establishing baselines of normal user and entity behavior and flagging deviations from those baselines using machine learning and advanced analytics. It identifies threats that traditional, rule-based systems might miss, such as the misuse of legitimate credentials or "low-and-slow" data exfiltration.
What is UEBA Offer :-
Key Benefits of Adding Entity Context in IBM QRadar UEBA :
Enhanced Threat Detection for Network Devices
Early Insider Threat Identification
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Monitors all trusted insider entities (endpoints, servers, etc.) for unusual access or data movement.
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Flags abnormal activities such as repeated failed login attempts or unusually large data transfers.
Entity Contextual Risk Scoring
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Dynamically assigns risk scores based on observed activities across network devices.
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Prioritizes alerts, enabling SOC teams to focus on entities with the highest risk levels.
Comprehensive Visibility
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Consolidates activities from users, devices, IPs, and applications into a unified behavioral profile.
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Provides entity-level dashboards for faster anomaly detection and investigation.
Extensive Use Case Coverage for UBA and UEBA
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200+ UBA rules are available out of the box, providing comprehensive coverage for user-based threat detection.
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30+ UEBA rules enhance this by adding entity-based analytics, enabling a combined view of both users and entities for more accurate and contextual threat detection.
Business Value
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Reduces risk exposure and minimizes financial impact from insider or advanced persistent threats (APT).
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Improves SOC efficiency, saving time and operational costs through a holistic view of users and entities.
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Strengthens organizational trust with customers and regulators through a proactive security posture.
Introducing holistic threat detection by combing user and entity risk context :
Use Case Example – Detecting Unauthorized Access Attempts :
In an organization, an internal or external user attempts to access a server containing confidential customer data, which they are not authorized to access. This activity could indicate a potential data exfiltration attempt.
The attacker may try to mask their identity using methods such as DHCP environments, changing IPs, or leveraging other techniques to evade detection.
However, QRadar UEBA intelligently correlates logs and behavioral patterns to identify both the entity (device) and the associated user involved in the suspicious activity. By combining user behavior analytics with entity context, UEBA provides a holistic view that helps SOC analysts quickly detect and respond to the threat.
This enables analysts to take immediate mitigation actions, such as:
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Blocking the unauthorized user
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Applying firewall policies to restrict access to sensitive servers or databases
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Preventing further suspicious movements within the network
As shown in the above image, let’s understand how QRadar UEBA identifies and responds to unauthorized access attempts through its advanced risk-based analytics.
QRadar UEBA continuously monitors anomalies triggered for all users and entities.In this case, Kevin (Sales Manager) and Peter (Marketing Executive) repeatedly attempt to access a database server that they are not authorized to access.
QRadar’s Custom Rule Engine (CRE) detects this suspicious activity and triggers the “UEBA: Unauthorized Access”rule, generating a sense event.
UEBA then ingests these sense events and, through its risk engine, automatically increases the risk scores for both the users (Kevin and Peter) and the targeted entity (DB server) — since multiple users are attempting to compromise it.
With the Entity Context View, SOC analysts gain a comprehensive picture that includes:
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🌍 Geolocation of the entity
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🖥️ Source IPs initiating the attack
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👥 Number of users associated with the incident
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⚠️ Overall risk score for both the entity and linked users
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⏱️ Attack timeline, showing frequency, timing, and rule violations
Once UEBA determines that the risk level is escalating, it automatically triggers alerts for both the affected users and the entity. This allows administrators to take timely preventive actions, such as blocking user access or isolating the compromised server.
Additionally, SOC analysts can review the overall health of the entity, including:
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Known vulnerabilities present on the system
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The vulnerability score, which helps prioritize remediation steps
This comprehensive insight enables faster incident response and proactive threat mitigation.
We explored one use case in detail, but there are 200+ use cases available for UBA and 30+ for UEBA. Together, these comprehensive scenarios help organizations effectively detect and prevent insider threats, strengthening their overall security posture.
High level data workflow and architecture for UEBA :-
Easy to Adopt for Existing QRadar Customers :
You can easily deploy the UEBA app in your existing QRadar environment.
Feel Free to reach out in case any questions and want to more deep dive in QRadar UEBA
Parth Shah - Software Architect
Email Id :- Parth.Anilbhai@ibm.com