This CS0-003 practice question tests your understanding of incident response and management. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which technology is specifically designed to detect anomalous user behavior that may indicate a compromised account?
IDS.
Why wrong: IDS monitors network traffic for signatures, not user behavior.
UEBA.
UEBA uses machine learning to detect anomalous user and entity behavior.
SIEM.
Why wrong: SIEM correlates logs but does not specialize in user behavior anomalies.
Antivirus.
Why wrong: Antivirus detects known malware, not behavioral anomalies.
Answer choices
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.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
IDS.
Why it's wrong here
IDS monitors network traffic for signatures, not user behavior.
UEBA.
Why this is correct
UEBA uses machine learning to detect anomalous user and entity behavior.
Related concept
Read the scenario before looking for a memorised answer.
SIEM.
Why it's wrong here
SIEM correlates logs but does not specialize in user behavior anomalies.
Antivirus.
Why it's wrong here
Antivirus detects known malware, not behavioral anomalies.
Common exam traps
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.
Detailed technical explanation
UEBA constructs a behavioral profile for each user by analyzing attributes such as login frequency, geolocation, device type, and access patterns over time. When a user's activity deviates significantly from their baseline—for example, a user who normally logs in from New York at 9 AM suddenly authenticates from a foreign country at 3 AM—UEBA assigns a risk score and triggers an alert. This approach is effective against credential theft and insider threats because it does not rely on known signatures, enabling detection of zero-day or low-and-slow attacks.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A security analyst at a medium-sized enterprise encounters this scenario during an investigation or architecture review. The correct answer reflects best practice for the specific threat or control described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Security exam questions test whether you can match controls to threats in context — not just recall definitions.
What to study next
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FAQ
Incident Response and Management — This question tests Incident Response and Management — Read the scenario before looking for a memorised answer..
The correct answer is: 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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 2026
This CS0-003 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 CS0-003 exam.
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