SC-200 Mitigate threats using Microsoft Sentinel Practice Question
This SC-200 practice question tests your understanding of mitigate threats using microsoft sentinel. 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.
A SOC analyst needs to create a custom alert in Microsoft Sentinel that triggers when a specific user logs in from an unusual geographic location, compared to a learned baseline of normal locations. Which type of analytics rule is best suited for this scenario?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Anomaly detection rule (machine learning)
Option C is correct because anomaly detection rules in Microsoft Sentinel use machine learning to establish a baseline of normal user behavior, such as typical geographic login locations. When a login event deviates significantly from this learned baseline, the rule triggers an alert. This is the only rule type specifically designed for detecting behavioral anomalies without requiring static thresholds or predefined patterns.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Scheduled query
Why it's wrong here
Scheduled queries run on a set frequency and use static thresholds, not adaptive learning of baselines.
✗
Near-real-time (NRT) rule
Why it's wrong here
NRT rules process data in near real-time but still rely on predefined conditions, not dynamic baselines.
✓
Anomaly detection rule (machine learning)
Why this is correct
Correct: This rule type uses ML to learn normal patterns and trigger alerts on deviations.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Fusion rule
Why it's wrong here
Fusion rules correlate alerts from multiple sources to detect multistage attacks, not single-sign-in anomalies.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse scheduled queries (Option A) with anomaly detection, assuming a KQL query using 'where Location != 'US'' can replace ML-based baseline learning, but scheduled queries cannot dynamically adapt to changing user behavior over time.
Detailed technical explanation
How to think about this question
Anomaly detection rules in Sentinel leverage the 'Anomalies' table, which is populated by machine learning models trained on historical data (e.g., Azure AD sign-in logs). The models use time-series decomposition and clustering algorithms to identify outliers, such as a login from a country never seen before for a specific user. Under the hood, Sentinel's ML engine calculates an anomaly score based on the deviation from the expected distribution, and only events exceeding a configurable threshold generate alerts.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this SC-200 question in full detail.
Mitigate threats using Microsoft Sentinel — This question tests Mitigate threats using Microsoft Sentinel — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Anomaly detection rule (machine learning) — Option C is correct because anomaly detection rules in Microsoft Sentinel use machine learning to establish a baseline of normal user behavior, such as typical geographic login locations. When a login event deviates significantly from this learned baseline, the rule triggers an alert. This is the only rule type specifically designed for detecting behavioral anomalies without requiring static thresholds or predefined patterns.
What should I do if I get this SC-200 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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