SC-200 Mitigate threats using Microsoft Sentinel Practice Test 1 — 15 Questions

Question 1

A security operations analyst is creating a scheduled analytics rule in Microsoft Sentinel to detect brute force attempts on Microsoft Entra ID authentication. Which data source is most appropriate for this rule?

Accepted Answer

SigninLogs. SigninLogs captures user authentication attempts to Microsoft Entra ID, including failed sign-ins, which are essential for detecting brute force attacks. This data source provides detailed properties such as IP address, application, and status codes (e.g., 50076 for invalid password), enabling accurate detection of repeated failed attempts. Azure Activity Logs, Office Activity Logs, and SecurityEvent do not contain Entra ID authentication events.

Answer

Azure Activity Logs

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Office Activity Logs

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SecurityEvent

Question 2

A security analyst wants to configure a playbook in Microsoft Sentinel that runs automatically when a specific alert is generated. Which trigger concept is used to invoke the playbook?

Accepted Answer

Azure Logic Apps trigger. In Microsoft Sentinel, playbooks are built on Azure Logic Apps, and the correct trigger to invoke a playbook automatically when an alert is generated is the Azure Logic Apps trigger. This trigger listens for the Sentinel alert creation event and initiates the playbook workflow. The other options are not valid trigger concepts within Sentinel's architecture.

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Sentinel trigger

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Alert trigger

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Automation rule trigger

Question 3

A security analyst is preparing to use a Jupyter notebook for threat hunting in Microsoft Sentinel. Which of the following sequences of actions is correct to start executing the notebook?

Accepted Answer

Provision compute → Clone Sentinel notebooks → Connect to workspace → Execute cells. Option A is correct because the correct sequence to start executing a Jupyter notebook for threat hunting in Microsoft Sentinel is to first provision compute (i.e., create a compute instance in Azure Machine Learning), then clone the Sentinel notebooks from the official GitHub repository, connect to the Sentinel workspace using the msticpy library, and finally execute the cells. This order ensures the compute environment is ready before loading the notebooks and establishing the workspace connection.

Answer

Clone Sentinel notebooks → Provision compute → Connect to workspace → Execute cells

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Connect to workspace → Provision compute → Clone Sentinel notebooks → Execute cells

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Provision compute → Connect to workspace → Clone Sentinel notebooks → Execute cells

Question 4

A security operations center (SOC) uses Microsoft Sentinel. The team wants to detect anomalous behavior for a specific user account that typically logs in only during business hours from a known IP range. They create a scheduled analytics rule that queries the SigninLogs table for logins outside that range or outside business hours. To reduce false positives, which of the following configurations should the analyst apply?

Accepted Answer

Set the alert threshold to 5 occurrences within the query lookback period.. Option A is correct because setting an alert threshold (e.g., 5 occurrences within the query lookback period) reduces false positives by requiring the anomalous behavior to be persistent rather than a single outlier. In Microsoft Sentinel, the alert threshold filters out noise from occasional legitimate logins that might accidentally fall outside business hours or the known IP range, ensuring the rule only fires when the pattern is repeated enough to indicate a real threat.

Answer

Enable entity mapping for the user account to correlate with other data sources.

Answer

Increase the query scheduling frequency to every 5 minutes from every hour.

Answer

Group all events into a single alert and set the suppression limit to 1 hour.

Question 5

A threat hunter in Microsoft Sentinel writes a KQL query in the Logs blade to find possible data exfiltration. The query uses the CommonSecurityLog table to look for large outbound file transfers from a specific IP address. The analyst wants to include only events where the total bytes sent in a 5-minute window exceed 100 MB. Which KQL operator combination would best achieve this?

Accepted Answer

CommonSecurityLog | where SourceIp == '10.0.0.1' | summarize totalBytes = sum(BytesSent) by bin(TimeGenerated, 5m) | where totalBytes > 100000000. Option A is correct because it first filters the CommonSecurityLog table for the specific source IP, then uses `summarize` with `bin(TimeGenerated, 5m)` to aggregate total bytes sent in 5-minute windows, and finally filters for windows where the sum exceeds 100 MB (100,000,000 bytes). This correctly implements a time-windowed aggregation to detect large outbound transfers, which is the standard pattern for identifying data exfiltration over a period.

Answer

CommonSecurityLog | where SourceIp == '10.0.0.1' | extend bin = bin(TimeGenerated, 5m) | where BytesSent > 100000000

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CommonSecurityLog | where SourceIp == '10.0.0.1' | summarize make_list(BytesSent) by TimeGenerated | where array_length(make_list) > 100000000

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CommonSecurityLog | where SourceIp == '10.0.0.1' | project BytesSent, TimeGenerated | summarize sum(BytesSent) by bin(TimeGenerated, 5m) | where sum_BytesSent > 100000000

Question 6

A SOC team uses Microsoft Sentinel and wants to ingest custom log events from an on-premises Linux application that writes to a local file. The team sets up the Log Analytics agent on the Linux server and configures a data connector. Which of the following is the necessary configuration step to collect the custom log file?

Accepted Answer

Use the Custom Logs feature in the Log Analytics workspace to specify the path to the application log file and define the log type name.. Option C is correct because the Custom Logs feature in the Log Analytics workspace is specifically designed to ingest text-based log files from on-premises Linux servers via the Log Analytics agent. You must specify the exact file path (e.g., /var/log/myapp.log) and define a custom log type name (e.g., MyApp_CL) to parse the file and send the data to a custom table in the Log Analytics workspace. This is the only method that directly collects custom application log files without requiring syslog or API-based ingestion.

Answer

Create a Syslog data connector and specify the facility and severity to filter the application logs from /var/log.

Answer

Configure the Log Analytics agent to collect performance counters for the application process.

Answer

Deploy a Log Analytics gateway and configure the application to write directly to the gateway using the HTTP Data Collector API.

Question 7

A security operations center (SOC) uses Microsoft Sentinel. The team wants to automatically assign incidents to the appropriate analyst based on the severity level of the alert. Which feature should be configured to achieve this automation?

Accepted Answer

Automation rules. Automation rules in Microsoft Sentinel allow you to define conditions (such as alert severity) and corresponding actions (like assigning an incident to a specific analyst or group) without requiring custom code. This directly meets the SOC's requirement to automatically route incidents based on severity levels, as automation rules can trigger on incident creation or update and perform assignment actions.

Answer

Playbooks

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Analytics rules

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Watchlists

Question 8

A SOC analyst in Microsoft Sentinel is creating a scheduled analytics rule to detect a possible password spray attack. The rule must trigger when a single source IP address has more than 10 failed logon attempts on different user accounts within a 30-minute window. The analyst writes a KQL query starting with 'SigninLogs | where ResultType == 50057' (failed logon). Which operator should the analyst use to group events by source IP and count distinct user accounts, then filter for counts above 10?

Accepted Answer

summarize. The `summarize` operator is required to group events by source IP address and count distinct user accounts using `dcount()` or `count()`. After summarizing, you apply a `where` clause to filter for counts above 10, which meets the rule's threshold. This is the standard pattern for aggregation in KQL.

Answer

where

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extend

Answer

project

Question 9

A SOC team uses Microsoft Sentinel. They need to correlate syslog events from on-premises firewalls with Microsoft Entra ID sign-in logs to detect VPN-based intrusions. The correlation requires joining two tables (Syslog and SigninLogs) on a common field (IP address) and running on a 10-minute schedule. Which type of analytics rule should the analyst configure?

Accepted Answer

Scheduled query rule. A scheduled query rule is correct because the requirement involves joining two tables (Syslog and SigninLogs) on a common field (IP address) and running on a 10-minute schedule. Scheduled query rules are designed for complex, multi-table correlations that run at fixed intervals (e.g., every 10 minutes) and can aggregate or join data across tables, making them ideal for this VPN intrusion detection scenario.

Answer

Near-real-time (NRT) rule

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Fusion rule

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Anomaly rule

Question 10

A security analyst is configuring a Microsoft Sentinel playbook to automate the response to phishing incidents. When an incident is created based on a phishing analytics rule, the playbook needs to execute an action in Microsoft 365 Defender, such as blocking the sender email address. Which connector should the analyst add to the playbook to interact with Microsoft 365 Defender?

Accepted Answer

Microsoft 365 Defender connector. The Microsoft 365 Defender connector is the correct choice because it provides the necessary actions to interact directly with Microsoft 365 Defender components, such as blocking a sender email address via the Advanced Hunting or action APIs. This connector enables the playbook to trigger remediation actions like email quarantine or sender block within the Microsoft 365 Defender portal, which is essential for automating responses to phishing incidents in Microsoft Sentinel.

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Microsoft Entra ID connector

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Azure DevOps connector

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Teams connector

Question 11

A security analyst in Microsoft Sentinel wants to create a custom analytics rule that triggers when more than 10 failed logon attempts from a single source IP address occur within 5 minutes. The analyst writes a KQL query to aggregate sign-in logs. Which KQL operator should the analyst use to group events by source IP and count each failure?

Accepted Answer

summarize. The `summarize` operator is correct because it groups rows by a specified key (source IP) and applies an aggregation function (like `count()`) to produce a single output row per group. In this scenario, the analyst needs to count failed logon attempts per source IP, which requires grouping and counting—exactly what `summarize` does.

Answer

extend

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project

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where

Question 12

A SOC team uses Microsoft Sentinel. They receive a large volume of low-severity incidents from a specific analytics rule that causes alert fatigue. They want to automatically close incidents that match certain criteria (e.g., originating from a known test IP). Which feature should they configure?

Accepted Answer

Automation rules with a condition to close incidents. Automation rules in Microsoft Sentinel allow you to automatically close incidents based on specific conditions, such as a known test IP address. This directly addresses alert fatigue by suppressing low-severity incidents without manual intervention. Unlike playbooks, automation rules are lightweight and run natively within Sentinel without requiring a Logic Apps instance.

Answer

Playbook with a timer trigger

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Watchlist integration

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Fusion rule

Question 13

A security analyst is configuring a playbook in Microsoft Sentinel to run automatically when a new incident of severity 'High' is created. The playbook should only run for incidents that are not already assigned to an analyst. How can the analyst configure this automation?

Accepted Answer

Create an automation rule with a condition on 'Owner' field equals 'Unassigned'. Option A is correct because Microsoft Sentinel automation rules can evaluate incident properties at creation time, including the 'Owner' field. By setting a condition that 'Owner' equals 'Unassigned', the rule triggers the playbook only for high-severity incidents that have not yet been assigned to an analyst, meeting the requirement without requiring custom logic inside the playbook.

Answer

Use a playbook trigger 'When a Microsoft Sentinel incident is created' and add a condition in the playbook

Answer

Configure a watchlist to filter incidents

Answer

Use a Logic Apps trigger for all incidents and check owner within the playbook

Question 14

A SOC team uses Microsoft Sentinel and wants to automate the response to high-severity incidents. When a new incident of severity 'High' is created, they need to send an email notification to the on-call analyst and assign the incident to that analyst. Which two components must be configured together to achieve this? (Choose the best answer.)

Accepted Answer

Automation rule and a playbook. Automation rules in Microsoft Sentinel allow you to define triggers based on incident creation or update, including severity conditions. By configuring an automation rule to trigger when a 'High' severity incident is created, you can run a playbook that sends an email to the on-call analyst and assigns the incident to them. This combination provides a no-code or low-code automated response without requiring a scheduled or Fusion rule.

Answer

Scheduled analytics rule and a playbook

Answer

Watchlist and an automation rule

Question 15

A security analyst in Microsoft Sentinel is creating a scheduled analytics rule to detect multiple failed logon attempts from the same source IP address. The rule should generate an incident only when the count of failed logons exceeds 10 within a 5-minute window. Which configuration setting is essential to limit the incident generation to this threshold?

Accepted Answer

Alert threshold set to a value of 10. The alert threshold setting in a Microsoft Sentinel scheduled analytics rule directly controls the minimum number of query results required to generate an incident. By setting the threshold to 10, the rule will only fire when the query returns more than 10 failed logon events within the 5-minute window, matching the requirement exactly.

Answer

Event grouping set to 'Group all events into a single alert'

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Query scheduling set to run every 5 minutes

Answer

Entity mapping for source IP address