- A
Create a playbook triggered by Microsoft Entra ID alerts.
Why wrong: Playbooks automate response, not detection rules.
- B
Write a custom KQL query using SigninLogs.
Why wrong: While possible, it requires more effort than using a built-in template.
- C
Configure a Microsoft Purview insider risk policy.
Why wrong: Purview policies focus on insider risks, not sign-in anomalies.
- D
Use a built-in Anomalous Sign-in Location rule template.
This template uses UEBA to detect anomalous sign-ins without custom KQL.
Quick Answer
The answer is to use the built-in Anomalous Sign-in Location rule template. This is the most efficient method because Microsoft Sentinel’s template is pre-configured with KQL logic that leverages Microsoft Entra ID Identity Protection risk data, automatically triggering an incident when a user signs in from an unfamiliar location without requiring custom development or additional data sources. On the SC-200 exam, this question tests your ability to identify when a built-in analytic rule can satisfy a detection requirement faster than writing a custom rule from scratch—a common trap is overcomplicating the solution by trying to build a custom KQL query when a ready-made template exists. Remember the memory tip: “Template first, custom last”—always check for a built-in rule before reinventing the wheel, especially for common scenarios like anomalous sign-in locations.
SC-200 Manage a security operations environment Practice Question
This SC-200 practice question tests your understanding of manage a security operations environment. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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.
Your team uses Microsoft Sentinel to investigate incidents. You need to create a custom analytic rule that triggers an incident when a user signs in from an unfamiliar location. What is the most efficient way to achieve this?
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
Use a built-in Anomalous Sign-in Location rule template.
Option D is correct because Microsoft Sentinel provides a built-in 'Anomalous Sign-in Location' rule template that leverages Microsoft Entra ID Identity Protection data to detect sign-ins from unfamiliar locations. This template is pre-configured with the necessary KQL logic and alerting, making it the most efficient method without requiring custom development or additional data sources.
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.
- ✗
Create a playbook triggered by Microsoft Entra ID alerts.
Why it's wrong here
Playbooks automate response, not detection rules.
- ✗
Write a custom KQL query using SigninLogs.
Why it's wrong here
While possible, it requires more effort than using a built-in template.
- ✗
Configure a Microsoft Purview insider risk policy.
Why it's wrong here
Purview policies focus on insider risks, not sign-in anomalies.
- ✓
Use a built-in Anomalous Sign-in Location rule template.
Why this is correct
This template uses UEBA to detect anomalous sign-ins without custom KQL.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may assume a custom KQL query (Option B) is the most flexible and efficient approach, overlooking that Sentinel's built-in templates are pre-optimized and require no manual logic for defining 'unfamiliar' locations.
Detailed technical explanation
How to think about this question
The 'Anomalous Sign-in Location' rule template in Sentinel uses Microsoft Entra ID Identity Protection's risk detection, which analyzes sign-in patterns against a user's historical behavior using machine learning models. This detection is based on properties like IP address, geolocation, and device fingerprint, and the rule automatically maps the risk level to incident severity. In a real-world scenario, this template reduces false positives by leveraging Microsoft's global threat intelligence and adaptive learning, which a custom KQL query would struggle to replicate without extensive tuning.
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 company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this SC-200 question test?
Manage a security operations environment — This question tests Manage a security operations environment — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use a built-in Anomalous Sign-in Location rule template. — Option D is correct because Microsoft Sentinel provides a built-in 'Anomalous Sign-in Location' rule template that leverages Microsoft Entra ID Identity Protection data to detect sign-ins from unfamiliar locations. This template is pre-configured with the necessary KQL logic and alerting, making it the most efficient method without requiring custom development or additional data sources.
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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 25, 2026
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