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CS0-003 Practice Question: Which technology is specifically designed to…
Which technology is specifically designed to detect anomalous user behavior that may indicate a compromised account?
⚠ Common exam trap
CompTIA often tests the distinction between correlation-based tools (SIEM) and behavior-based tools (UEBA), and the trap here is that candidates confuse SIEM's log aggregation and rule-based alerting with UEBA's machine learning-driven anomaly detection for user behavior.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
UEBA.
User and Entity Behavior Analytics (UEBA) is specifically designed to establish baselines of normal user behavior and detect anomalous activities—such as unusual login times, impossible travel, or abnormal data access patterns—that may indicate a compromised account. Unlike signature-based tools, UEBA leverages machine learning and statistical modeling to identify deviations from established norms, making it the correct choice for detecting account compromise.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
IDS.
Why it's wrong here
An Intrusion Detection System (IDS) primarily operates by monitoring network traffic or system activities for known attack signatures or policy violations. While it can detect suspicious patterns, its core function is not to establish baselines of normal user behavior and identify deviations from those baselines. Therefore, an IDS is not specifically designed for detecting anomalous user behavior, but rather known malicious network or system events.
- ✓
UEBA.
Why this is correct
User and Entity Behavior Analytics (UEBA) is specifically engineered to detect anomalous activities by establishing baselines of normal behavior for users and other entities within an organization's IT environment. It employs machine learning algorithms and statistical analysis to identify deviations from these baselines, such as unusual login times, access to sensitive data, or data exfiltration attempts, which often indicate compromised accounts or insider threats. This makes UEBA the ideal technology for proactive detection of behavioral anomalies.
- ✗
SIEM.
Why it's wrong here
A Security Information and Event Management (SIEM) system aggregates and correlates security event data from various sources across an organization's infrastructure, including logs, network devices, and applications. While a SIEM can ingest data that UEBA generates and might perform some rule-based correlation, its primary function is not to autonomously profile individual user or entity behavior and apply advanced analytics to detect subtle, statistically significant anomalies. It provides a holistic view but lacks the specialized behavioral intelligence of UEBA.
- ✗
Antivirus.
Why it's wrong here
Antivirus software is primarily designed to prevent, detect, and remove malicious software, such as viruses, worms, and Trojans, from endpoints. It largely relies on signature-based detection, comparing files against a database of known malware, or heuristic analysis for suspicious file characteristics. Antivirus solutions are not equipped to establish baselines of normal user activity or to identify deviations in user behavior patterns that might indicate a compromised account or an insider threat.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This CS0-004 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the CS0-004 exam.