- A
SigninLogs | join ThreatIntelligence_IP on IPAddress | where UserId notin (ApprovedUsers | project UserId)
Why wrong: This uses a subquery to filter UserId, but it does not use a proper anti-join; the 'notin' operator may be inefficient and not as clear as an anti-join.
- B
SigninLogs | where IPAddress in (ThreatIntelligence_IP | project IPAddress) and UserId !in (ApprovedUsers | project UserId)
Why wrong: Using 'in' and '!in' with subqueries is valid but less performant than joins for large tables. Also, '!in' is not a KQL operator; the correct operator is '!in' is not valid; should be 'notin'.
- C
SigninLogs | join kind=inner ThreatIntelligence_IP on IPAddress | join kind=leftanti (ApprovedUsers | project UserId) on $left.UserId == $right.UserId
This query first performs an inner join to keep only sign-ins from threat actor IPs, then a left anti join to exclude sign-ins from approved users. This is the most efficient and clear pattern.
- D
SigninLogs | join ThreatIntelligence_IP on IPAddress | where not(UserId in (ApprovedUsers | project UserId))
Why wrong: While this works logically, using a join followed by a 'where not in' subquery is less efficient than an anti-join.
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 security analyst in Microsoft Sentinel wants to correlate Microsoft Entra ID sign-in logs with IP addresses known to be associated with a threat actor. The threat actor's IPs are stored in a custom table named 'ThreatIntelligence_IP' that is ingested daily. The analyst needs to create an analytics rule that triggers only when a sign-in occurs from one of these IPs AND when the user is not in a list of approved users (stored in another custom table 'ApprovedUsers'). Which KQL query pattern should the analyst use to achieve this correlation and filtering?
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
SigninLogs | join kind=inner ThreatIntelligence_IP on IPAddress | join kind=leftanti (ApprovedUsers | project UserId) on $left.UserId == $right.UserId
Option C is correct because it uses a `join kind=inner` to match sign-in logs with threat IPs, ensuring only sign-ins from known malicious IPs are considered. It then applies a `join kind=leftanti` to exclude any user who appears in the ApprovedUsers table, effectively filtering out approved users. This pattern guarantees that the rule triggers only when both conditions are met: the IP is in the threat list and the user is not approved.
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.
- ✗
SigninLogs | join ThreatIntelligence_IP on IPAddress | where UserId notin (ApprovedUsers | project UserId)
Why it's wrong here
This uses a subquery to filter UserId, but it does not use a proper anti-join; the 'notin' operator may be inefficient and not as clear as an anti-join.
- ✗
SigninLogs | where IPAddress in (ThreatIntelligence_IP | project IPAddress) and UserId !in (ApprovedUsers | project UserId)
Why it's wrong here
Using 'in' and '!in' with subqueries is valid but less performant than joins for large tables. Also, '!in' is not a KQL operator; the correct operator is '!in' is not valid; should be 'notin'.
- ✓
SigninLogs | join kind=inner ThreatIntelligence_IP on IPAddress | join kind=leftanti (ApprovedUsers | project UserId) on $left.UserId == $right.UserId
Why this is correct
This query first performs an inner join to keep only sign-ins from threat actor IPs, then a left anti join to exclude sign-ins from approved users. This is the most efficient and clear pattern.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
SigninLogs | join ThreatIntelligence_IP on IPAddress | where not(UserId in (ApprovedUsers | project UserId))
Why it's wrong here
While this works logically, using a join followed by a 'where not in' subquery is less efficient than an anti-join.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose Option B thinking that `in` and `!in` with subqueries are the simplest way to filter, but they overlook that KQL requires proper join semantics for correlating two tables, and that `in` with a table expression may not work as expected in all contexts, especially when the subquery returns multiple rows or columns.
Detailed technical explanation
How to think about this question
The `leftanti` join is a semi-join that returns all records from the left table that do not have a match in the right table, making it ideal for exclusion scenarios like removing approved users. Under the hood, KQL optimizes this join by building a hash table from the right side, allowing efficient lookups. In real-world threat hunting, using `leftanti` avoids the need for a separate `where` clause and ensures that the exclusion logic is part of the join, which can be more performant with large datasets.
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
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FAQ
Questions learners often ask
What does this SC-200 question test?
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: SigninLogs | join kind=inner ThreatIntelligence_IP on IPAddress | join kind=leftanti (ApprovedUsers | project UserId) on $left.UserId == $right.UserId — Option C is correct because it uses a `join kind=inner` to match sign-in logs with threat IPs, ensuring only sign-ins from known malicious IPs are considered. It then applies a `join kind=leftanti` to exclude any user who appears in the ApprovedUsers table, effectively filtering out approved users. This pattern guarantees that the rule triggers only when both conditions are met: the IP is in the threat list and the user is not approved.
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 11, 2026
This SC-200 practice question is part of Courseiva's free Microsoft 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 SC-200 exam.
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