- A
SigninLogs, summarize make_set(Country) by UserPrincipalName, then where countof(Country) > 3
Why wrong: make_set creates an array, and countof on the array gives the distinct count, but this does not account for the time window (10 minutes).
- B
SigninLogs, summarize dcount(Country) by UserPrincipalName, bin(TimeGenerated, 10m) having dcount > 3
This correctly groups sign-in attempts by user and 10-minute bins, then counts distinct countries and filters for >3.
- C
AADSignInEventsMicrosoft, summarize count() by UserPrincipalName
Why wrong: This table is designed for advanced hunting in Microsoft 365 Defender and is not the standard table for scheduled analytics rules in Sentinel. It also does not include a country field in the same way.
- D
AzureActivity, summarize make_list(Country) by Caller
Why wrong: AzureActivity tracks Azure resource operations, not user sign-in events, and does not contain a Country field.
Quick Answer
The correct answer is the combination of the `SigninLogs` table with `summarize dcount(Country) by UserPrincipalName, bin(TimeGenerated, 10m)` and a `having dcount > 3` clause, because this directly performs the impossible travel detection by counting distinct countries per user within a strict 10-minute window. The `SigninLogs` table stores Azure AD authentication events complete with geographic location data, while `dcount()` provides an efficient approximate distinct count, and `bin()` groups timestamps into 10-minute buckets to enforce the time constraint. On the SC-200 exam, this question tests your ability to combine time-based aggregation with geographic filtering for threat detection—a common scenario in Microsoft Sentinel analytics rules. A frequent trap is forgetting the `having` clause or using `where` instead, which would incorrectly filter rows before aggregation rather than after. Memory tip: think "Bin, Dcount, Having" as the three-step rhythm for any time-windowed geographic anomaly rule.
SC-200 Mitigate threats using Microsoft Sentinel Practice Question
This SC-200 practice question tests your understanding of mitigate threats using microsoft sentinel. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. A key principle to apply: the `SigninLogs` table is the primary source for Azure AD sign-in data in Sentinel.. 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 an analytics rule in Microsoft Sentinel that triggers when a single user attempts to sign in from more than three different countries within 10 minutes. Which tables and KQL operators are needed?
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, summarize dcount(Country) by UserPrincipalName, bin(TimeGenerated, 10m) having dcount > 3
Option B is correct because it uses the `SigninLogs` table, which contains Azure AD sign-in events with geographic data, and the `summarize dcount(Country) by UserPrincipalName, bin(TimeGenerated, 10m)` pattern to count distinct countries per user within a 10-minute window. The `having dcount > 3` clause filters for users who signed in from more than three distinct countries, directly matching the requirement.
Key principle: The `SigninLogs` table is the primary source for Azure AD sign-in data in Sentinel.
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, summarize make_set(Country) by UserPrincipalName, then where countof(Country) > 3
Why it's wrong here
make_set creates an array, and countof on the array gives the distinct count, but this does not account for the time window (10 minutes).
- ✓
SigninLogs, summarize dcount(Country) by UserPrincipalName, bin(TimeGenerated, 10m) having dcount > 3
Why this is correct
This correctly groups sign-in attempts by user and 10-minute bins, then counts distinct countries and filters for >3.
Related concept
The `SigninLogs` table is the primary source for Azure AD sign-in data in Sentinel.
- ✗
AADSignInEventsMicrosoft, summarize count() by UserPrincipalName
Why it's wrong here
This table is designed for advanced hunting in Microsoft 365 Defender and is not the standard table for scheduled analytics rules in Sentinel. It also does not include a country field in the same way.
- ✗
AzureActivity, summarize make_list(Country) by Caller
Why it's wrong here
AzureActivity tracks Azure resource operations, not user sign-in events, and does not contain a Country field.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse `count()` (total events) with `dcount()` (distinct values) and overlook the need for `bin()` to enforce the time window, leading them to choose Option A or C despite their invalid syntax or wrong table.
Detailed technical explanation
How to think about this question
The `dcount()` function uses the HyperLogLog algorithm to estimate distinct values efficiently, which is critical for real-time analytics on high-volume sign-in logs. The `bin(TimeGenerated, 10m)` creates fixed 10-minute buckets, ensuring that sign-ins are grouped into non-overlapping windows; without it, the aggregation would span the entire dataset. In a real-world scenario, this rule detects credential-stuffing or token-replay attacks where an attacker rapidly tests credentials from geographically distributed proxies.
KKey Concepts to Remember
- The `SigninLogs` table is the primary source for Azure AD sign-in data in Sentinel.
- `bin(TimeGenerated, 10m)` groups events into 10-minute intervals for temporal analysis.
- `dcount()` efficiently calculates the number of distinct values in a group.
- `having` filters results of aggregation functions, like `dcount`.
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
The `SigninLogs` table is the primary source for Azure AD sign-in data in Sentinel.
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. The `SigninLogs` table is the primary source for Azure AD sign-in data in Sentinel. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
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?
Mitigate threats using Microsoft Sentinel — This question tests Mitigate threats using Microsoft Sentinel — The `SigninLogs` table is the primary source for Azure AD sign-in data in Sentinel..
What is the correct answer to this question?
The correct answer is: SigninLogs, summarize dcount(Country) by UserPrincipalName, bin(TimeGenerated, 10m) having dcount > 3 — Option B is correct because it uses the `SigninLogs` table, which contains Azure AD sign-in events with geographic data, and the `summarize dcount(Country) by UserPrincipalName, bin(TimeGenerated, 10m)` pattern to count distinct countries per user within a 10-minute window. The `having dcount > 3` clause filters for users who signed in from more than three distinct countries, directly matching the requirement.
What should I do if I get this SC-200 question wrong?
Review the `SigninLogs` table is the primary source for Azure AD sign-in data in Sentinel., then practise related SC-200 questions on the same topic to reinforce the concept.
What is the key concept behind this question?
The `SigninLogs` table is the primary source for Azure AD sign-in data in Sentinel.
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Last reviewed: Jun 11, 2026
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