SC-200 Perform threat hunting Practice Question
A security team uses Microsoft Sentinel to hunt for signs of credential theft. They want to detect when a user account has been used to log in from an unusual location and then immediately performs a password reset for another user. Which hunting approach is most effective for this scenario?
⚠ Common exam trap
SC-200 often tests whether candidates understand that effective hunting requires correlating multiple log sources — the trap is selecting a single-table query or an automation that lacks the temporal and cross-table correlation needed to detect multi-step attack patterns.
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
✓
Write a KQL query that joins SigninLogs with AuditLogs on user principal name and times within a short window
The most effective hunting approach is a KQL query that correlates SigninLogs (login events, including location) with AuditLogs (password reset operations) by joining on UserPrincipalName and filtering for events within a short time window. This detects the specific behavioral pattern: an unusual-location login immediately followed by a password reset for another user, which is a classic credential theft and privilege abuse indicator.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use a Microsoft Sentinel playbook to automatically flag any password reset
Why it's wrong here
A playbook flags every password reset indiscriminately, so it cannot correlate an unusual-location sign-in with a subsequent reset by the same actor, missing the behavioural sequence entirely. Playbooks suit automated response actions once a detection fires, not the correlation logic itself.
- ✓
Write a KQL query that joins SigninLogs with AuditLogs on user principal name and times within a short window
Why this is correct
Joining SigninLogs and AuditLogs on user principal name, constrained to a short time window, correlates an anomalous sign-in with a subsequent password reset. This temporal correlation across both tables surfaces the credential-theft sequence, which neither log alone reveals.
- ✗
Search the SigninLogs table for logins from unusual locations
Why it's wrong here
Searching SigninLogs alone surfaces the anomalous location but never correlates it with the subsequent password-reset action, so the two-event sequence in the stem goes undetected. SigninLogs is the right source when the requirement is solely to identify risky or atypical sign-ins, not to link a login to follow-on activity in another table.
- ✗
Create a watchlist of known unusual locations and use it in a query against AuditLogs
Why it's wrong here
A static watchlist of known unusual locations cannot identify the anomalous sign-in, because the stem requires detecting an unusual location dynamically rather than matching pre-listed ones. Watchlists suit enriching queries with reference data such as VIP lists or known-bad IPs.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
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