Microsoft MS-102 Exam Dumps, Practice Test Questions

Inspect discovered apps, app risk indicators and associated user/traffic patterns. is directed at a separate task: A manager asks which shadow SaaS application poses the greatest risk to the business. It does not produce the required configuration outcome: False positive alerts decline without suppressing the core suspicious behavior.

Integrate eligible endpoint discovery data for remote devices and validate ingestion. implements a different mechanism for: An organization wants Cloud Discovery data for remote laptops that never traverse corporate firewalls. It does not configure the mechanism needed here: Tune policy conditions based on actual Cloud Apps alert dispositions.

Deploy the specific ASR rule with an approved mode to the appropriate device group. is directed at a separate task: Administrators want an endpoint attack-surface reduction rule to restrict risky behaviors. It does not produce the required configuration outcome: False positive alerts decline without suppressing the core suspicious behavior.

Its discovered-app classification now reflects the organization's explicit approval. would assess a different control. In this case it does not rule out the specific failure: The team disables all Cloud Apps alert policies after one noisy detection.

The discovered-app report reflects cloud usage from off-network endpoints. is evidence of another system state: An organization wants Cloud Discovery data for remote laptops that never traverse corporate firewalls. The acceptance evidence here instead is: False positive alerts decline without suppressing the core suspicious behavior.

The timeline identifies who isolated or remediated the affected device and when. would assess a different control. In this case it does not rule out the specific failure: The team disables all Cloud Apps alert policies after one noisy detection.

The discovery report was not examined at the per-user or per-source level. would fit a different circumstance involving: A Cloud Discovery report shows a risky service but the team needs to know which employees used it. Here the actual symptom is: The team disables all Cloud Apps alert policies after one noisy detection.

Conditional Access App Control session routing or applicability was not configured. is a plausible failure in another case: A policy was defined but the browser session never reached Cloud Apps controls. It does not explain the current incident: The team disables all Cloud Apps alert policies after one noisy detection.

Incident severity and ownership were not incorporated into the triage process. would fit a different circumstance involving: A SOC lead needs to triage open incidents according to impact and urgency rather than creation time alone. Here the actual symptom is: The team disables all Cloud Apps alert policies after one noisy detection.

Use discovered app usage drilldowns with user and source evidence. can be useful when a Cloud Discovery report shows a risky service but the team needs to know which employees used it. However, it does not specifically achieve: Its discovered-app classification now reflects the organization's explicit approval.

Review Cloud Discovery app risk scoring and usage evidence. addresses another administrative need: A manager asks which shadow SaaS application poses the greatest risk to the business. This question instead requires the outcome: Its discovered-app classification now reflects the organization's explicit approval.

Compare onboarded devices against expected device inventory and sensor-health status. can be useful when security wants to track whether the Defender endpoint agent is enabled on recently provisioned machines. However, it does not specifically achieve: Its discovered-app classification now reflects the organization's explicit approval.

Filter the activity log for download operations, user and timeframe. is directed at a separate task: An analyst needs to see which administrator downloaded sensitive files from a connected cloud application. It does not produce the required configuration outcome: Its discovered-app classification now reflects the organization's explicit approval.

Open the anomaly alert and examine IP, geography, timestamps and known benign causes. implements a different mechanism for: An analyst sees an impossible-travel alert for a user with two distant sign-ins. It does not configure the mechanism needed here: Apply a Sanctioned classification after the app passes organizational review.

Open the device timeline and filter around the incident time and event type. is directed at a separate task: An endpoint security analyst wants to inspect the processes that executed before a malware incident. It does not produce the required configuration outcome: Its discovered-app classification now reflects the organization's explicit approval.

Eligible sessions are controlled and the disallowed download action is blocked. would assess a different control. In this case it does not rule out the specific failure: Approved business software continues to be flagged as an unsanctioned exception.

The review distinguishes high-risk applications from approved low-risk services. is evidence of another system state: A manager asks which shadow SaaS application poses the greatest risk to the business. The acceptance evidence here instead is: Its discovered-app classification now reflects the organization's explicit approval.

The specific affected devices and fixed-version recommendation are recorded. would assess a different control. In this case it does not rule out the specific failure: Approved business software continues to be flagged as an unsanctioned exception.

The app was not formally marked unsanctioned in Cloud Apps policy workflow. would fit a different circumstance involving: A company wants to mark an investigated cloud app as prohibited for corporate use. Here the actual symptom is: Approved business software continues to be flagged as an unsanctioned exception.

Cloud Discovery lacks the supported network or endpoint telemetry source. is a plausible failure in another case: A shadow SaaS service remains invisible because no traffic source is connected. It does not explain the current incident: Approved business software continues to be flagged as an unsanctioned exception.

The email investigation skipped the relevant message/entity evidence. would fit a different circumstance involving: An analyst is investigating one reported phishing message and needs sender, URL and recipient details. Here the actual symptom is: Approved business software continues to be flagged as an unsanctioned exception.

Use Cloud Discovery from supported endpoint or firewall/proxy telemetry. can be useful when security must discover unsanctioned cloud services used through corporate network traffic. However, it does not specifically achieve: The team identifies both the policy condition and the user action that triggered it.

Apply a Sanctioned classification after the app passes organizational review. addresses another administrative need: A discovered app is safe for a specific business group and should no longer be treated as shadow IT. This question instead requires the outcome: The team identifies both the policy condition and the user action that triggered it.

Hunt for the relevant Microsoft 365 email or URL-click events in Defender XDR. can be useful when an incident handler sees unusual email links and wants to correlate click telemetry with a specific phishing campaign. However, it does not specifically achieve: The team identifies both the policy condition and the user action that triggered it.

Inspect discovered apps, app risk indicators and associated user/traffic patterns. is directed at a separate task: A manager asks which shadow SaaS application poses the greatest risk to the business. It does not produce the required configuration outcome: The team identifies both the policy condition and the user action that triggered it.

Configure the supported Cloud Discovery data source and analyze discovered services. implements a different mechanism for: Security must discover unsanctioned cloud services used through corporate network traffic. It does not configure the mechanism needed here: Use Cloud Apps policy alerts to detect patterns and activity logs to inspect specific actions.

Add the malicious file indicator with a block action and intended scope. is directed at a separate task: A suspicious file hash must be blocked across eligible onboarded devices. It does not produce the required configuration outcome: The team identifies both the policy condition and the user action that triggered it.

The app appears classified as unsanctioned and eligible enforcement blocks its use. would assess a different control. In this case it does not rule out the specific failure: The analyst treats an aggregated policy alert as proof of an exact user click without viewing the event.

Its discovered-app classification now reflects the organization's explicit approval. is evidence of another system state: A discovered app is safe for a specific business group and should no longer be treated as shadow IT. The acceptance evidence here instead is: The team identifies both the policy condition and the user action that triggered it.

The device reports onboarded status and begins sending endpoint telemetry. would assess a different control. In this case it does not rule out the specific failure: The analyst treats an aggregated policy alert as proof of an exact user click without viewing the event.

App discovery risk and actual usage evidence were not evaluated. would fit a different circumstance involving: A manager asks which shadow SaaS application poses the greatest risk to the business. Here the actual symptom is: The analyst treats an aggregated policy alert as proof of an exact user click without viewing the event.

The Cloud Discovery data collection excludes roaming endpoint traffic. is a plausible failure in another case: Remote users' SaaS traffic is absent because only office firewall logs are ingested. It does not explain the current incident: The analyst treats an aggregated policy alert as proof of an exact user click without viewing the event.

Policy assignment was mistaken for successful device-side application. would fit a different circumstance involving: A Defender endpoint configuration appears deployed, but the devices are still in an unsafe state. Here the actual symptom is: The analyst treats an aggregated policy alert as proof of an exact user click without viewing the event.