SC-200 Exam Dumps - Microsoft Security Operations Analyst

To show labeled files from Windows 10 endpoints in the Azure Information Protection – Data discovery dashboard, you must first enable the built-in integration between Microsoft Defender for Endpoint and Azure Information Protection (AIP). This is turned on in the Microsoft Defender Security Center under Settings → Advanced features. When enabled, Defender for Endpoint inventories sensitivity labels seen on files across managed Windows devices and streams that telemetry to the AIP Data discovery experience, providing visibility into where labeled data resides on endpoints. Scanner clusters and content scan jobs in AIP are intended for on-premises repositories (file shares/SharePoint servers), not for endpoint discovery. Device health/compliance reports do not surface or forward label inventory to AIP. Therefore, the first configuration step is enabling the AIP integration advanced feature in Defender for Endpoint so labeled files on Windows clients appear in the AIP Data discovery dashboard.

The problem described in the case study states that “Cloud App Security frequently generates false positive alerts when users connect to both offices simultaneously.” This behavior is commonly associated with the “Impossible travel” anomaly detection policy in Microsoft Defender for Cloud Apps.

According to Microsoft documentation, the “Impossible travel” policy detects when a user signs in from two locations that are geographically distant within an unrealistic timeframe. However, in multi-office environments (such as Boston and Seattle) or when VPN connections are used, this policy can frequently trigger false positives, since it may misinterpret legitimate connections as anomalous.

Microsoft recommends adjusting the impossible travel detection policy to account for trusted IP ranges, known locations, or VPN endpoints to reduce false alerts. Specifically, administrators can modify the policy’s sensitivity, include the organization’s office IP addresses as trusted, and exclude known network ranges.

This approach directly aligns with the case study’s scenario and satisfies the Defender for Cloud Apps requirement to reduce false positives while maintaining user anomaly detection accuracy.

✅ Final Answer for Question 3: D. Impossible travel

To restrict cloud apps running on CLIENT1 (a Windows 10 endpoint) in compliance with Microsoft Defender for Endpoint (MDE) requirements, you must integrate Microsoft Defender for Endpoint with Microsoft Defender for Cloud Apps (formerly Cloud App Security) using Cloud Discovery. This integration enables the blocking of unsanctioned cloud apps through the endpoint’s network protection capabilities.

According to Microsoft Defender for Cloud Apps documentation, Cloud Discovery uses traffic data from Defender for Endpoint to identify and manage the use of shadow IT. The relevant steps include:

1️⃣ Enable advanced features in Microsoft Defender for Endpoint (M365 Defender portal → Settings → Endpoints → Advanced features).

You must enable the following advanced features:

Microsoft Defender for Cloud Apps integration

Network protection (in block mode)

Custom network indicators (if applicable)These options allow Defender for Endpoint to share telemetry and enforce app restrictions received from Defender for Cloud Apps.

2️⃣ Configure Cloud Discovery settings in Microsoft Defender for Cloud Apps.

In the Defender for Cloud Apps portal, Cloud Discovery must be configured to receive continuous reports from Defender for Endpoint devices. Within these settings, you define sanctioned and unsanctioned applications. Once an app is marked as unsanctioned, Defender for Endpoint enforces blocking on all onboarded devices (like CLIENT1).

This two-part configuration ensures that MDE enforces the blocking of unsanctioned cloud applications discovered through Cloud App Security telemetry, fulfilling the business requirement that “All Cloud App Security unsanctioned apps must be blocked on the Windows 10 computers by using Microsoft Defender for Endpoint.”

The test analytics rule must generate alerts for inbound Office 365 access by several test users and group those alerts into separate incidents—one per user. In Azure Sentinel, incident grouping by entity depends on the rule’s Entity mapping. When you create a scheduled analytics rule, under Set rule logic you map columns from your query to entities like Account, IP, or Host. Once mapped, you can configure Event grouping so alerts with the same entity value (e.g., the same Account) are automatically grouped into a single incident. Turning suppression on/off or changing severity/tactics doesn’t influence entity-based incident grouping. Therefore, to ensure “one incident per test user account,” you must map the Account entity (and any other relevant entities) in Set rule logic, then enable grouping by that entity—fulfilling the Sentinel requirement.QUESTION NO: 3 HOTSPOT

You need to create the analytics rule to meet the Azure Sentinel requirements.

What should you do? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Answer:

According to Microsoft Security Operations (SecOps) and Azure Sentinel documentation, when you need to create an analytics rule that executes a custom KQL query and automatically initiates a playbook, the correct configuration is to create a Scheduled rule and ensure the playbook includes a trigger.

Here’s why:

A Scheduled analytics rule in Microsoft Sentinel (Microsoft Defender XDR portal) is designed for running custom KQL queries at defined intervals (for example, every hour or every few minutes) to detect specific patterns of suspicious activity. When the rule’s conditions are met, Sentinel generates alerts that can automatically trigger a playbook for response and automation.

A playbook in Sentinel is an Azure Logic App that automates responses to incidents or alerts. To connect a playbook to an analytics rule, it must include a trigger—specifically, the “Microsoft Sentinel Alert” or “Incident trigger.” This allows the rule to start the playbook automatically when the defined condition is met.

The other options are incorrect because:

Fusion rules are built-in and use Microsoft’s machine learning to correlate signals automatically; they can’t be used for custom queries.

Microsoft incident creation rules are also built-in and handle alert-to-incident grouping logic, not custom query execution.

A service principal would be needed for permissions (e.g., admin1 configuring playbooks), but not inside the playbook itself.

Diagnostics settings apply to log collection and retention, not rule automation.

Therefore, based on Microsoft Sentinel best practices and documentation:

✅ Create the rule of type: Scheduled

✅ Configure the playbook to include: A trigger

To integrate Microsoft Defender for Cloud Apps (MCAS) with Microsoft Sentinel, Microsoft’s official SecOps and Sentinel documentation specifies a two-step configuration process.

In the Defender for Cloud Apps portal – You add a security extension to enable integration with external SIEM platforms. This action allows MCAS to forward its alerts, activities, and discovered app telemetry to other Microsoft or third-party security platforms. By adding the security extension, Defender for Cloud Apps is authorized to send data streams and alerts to Microsoft Sentinel through a supported API connection.

In Microsoft Sentinel (Azure portal) – You then add a data connector. Data connectors in Sentinel are predefined integration pipelines that bring in telemetry from Microsoft or external security solutions. The Microsoft Defender for Cloud Apps connector specifically ingests MCAS alerts and audit logs into Sentinel, where they can be correlated with other Microsoft Defender XDR signals, enabling unified detection and investigation across identity, endpoint, and cloud layers.

This integration approach adheres to Microsoft’s principle of minimizing administrative effort by using native connectors rather than custom ingestion or log collector configurations. Once connected, Sentinel automatically normalizes MCAS alerts into its SecurityAlert and CloudAppEvents tables for rule creation, playbook automation, and incident correlation.

Therefore, the verified correct configuration is:

Defender for Cloud Apps: Add a security extension

Sentinel: Add a data connector

ï‚· Log Analytics workspace to use: LA1

ï‚· Windows security events to collect: All Events

To meet the Azure Defender (Microsoft Defender for Cloud) requirement that all servers send logs to the same Log Analytics workspace, you should select the existing workspace LA1. Defender for Cloud best practices recommend centralizing data in a single workspace for unified analytics, incident correlation, and cost control. Using the “Default workspace created by Azure Security Center” or creating a new workspace would fragment telemetry, complicate management, and contradict the stated requirement and the business goal to minimize costs (multiple workspaces can increase ingestion/retention overhead and complicate RBAC and automation).

For Windows hosts, Defender for Cloud’s Data collection setting controls the level of Windows Security Events collected: Minimal, Common, or All Events. The business requirement calls for logs that provide a full audit trail of user activities. In Microsoft guidance, All Events is the level intended for comprehensive auditing (including logon/logoff, account changes, privilege use, process creation, object access, and other advanced categories). Therefore, to satisfy the “full audit trail” requirement and ensure complete visibility for investigations and Sentinel analytics, choose All Events.

In summary: centralize on LA1 (single workspace) and collect All Events to achieve both operational and compliance objectives with Defender for Cloud and Sentinel.

According to Microsoft Defender for Cloud (formerly Azure Security Center) documentation, when integrating servers and virtual machines for security monitoring, the Defender for Cloud data is stored and analyzed in a Log Analytics workspace. Microsoft best practices recommend using an existing workspace when one is already deployed for centralized log collection—especially if it already gathers telemetry from Azure and on-premises resources.

In this case, the existing workspace LA1 already “contains logs and metrics collected from all Azure resources and on-premises servers.” This satisfies the business requirement of “all servers must send logs to the same Log Analytics workspace.” Creating a new workspace would violate the cost-minimization and centralization requirements. Therefore, LA1 is the correct workspace to use.

For the Windows security events collection setting, Defender for Cloud offers three levels:

Minimal – collects essential security events only (insufficient for comprehensive monitoring).

Common – collects a balanced set of security-related events (such as account logon, privilege use, and object access), recommended by Microsoft for most environments.

All Events – collects every possible security event, which increases data ingestion cost and is typically used only for high-security or regulated environments.

Because Litware Inc. must minimize cost while ensuring a full audit trail of user activities, the Common level provides the optimal balance of visibility and cost efficiency.

Therefore, based on Microsoft Defender for Cloud configuration guidelines:

✅ Log Analytics workspace to use: LA1

✅ Windows security events to collect: Common