Microsoft Updated SC-200 Exam Questions and Answers by yaqub

 Internal threat: Modify the access policy settings for the key vault.

 External threat: Modify the Key Vault firewall s ettings.

For internal threats involving a potential compromise of Fabrikam’s own Azure AD applications, the most direct and least disruptive remediation is to modify the Key Vault access policies (or RBAC assignments, if RBAC for Key Vault data-plane is in use) to immediately remove or reduce the compromised service principal’s permissions (Get/List/Decrypt/Sign/Wrap). Microsoft guidance for Key Vault access emphasizes least privilege and promptly revoking credentials or app permissions when compromise i s suspected. Access policies (or data-plane RBAC) govern which identities can access secrets, keys, and certificates; adjusting these stops further data-plane actions by the compromised app. “Resource locks” protect against deletion or configuration change s at the management plane, but they do not remove a compromised identity’s ability to read or use vault objects, so they are not an appropriate first response for this scenario.

For external threats , Microsoft recommends hardening Key Vault firewall and networking : restrict public network access, allow only required IPs, use virtual network rules, and prefer private endpoints. Key Vault includes a built-in firewall for IP and VNet ACLs; tuning these controls reduces exposure to the public internet and blo cks unauthorized traffic. NSGs apply to IaaS subnets/nics and don’t directly secure the public Key Vault endpoint. Azure Firewall can add perimeter control, but it is not necessary for remediating a specific Key Vault Defender alert; the most effective and immediate remediation is tightening the Key Vault firewall settings to limit external access pathways.

In Microsoft Sentinel (built on Azure Monitor Logs), analytics and hunting queries are executed within a Log Analytics workspace . To run Sentinel queries for Fabrikam, the tenant must have at least one workspace (with Sentinel enabled) in its subscription to host rules, incidents, hunting queries, and workbooks. Sentinel’ s cross-workspace/tenant capability is provided by cross-resource queries in Kusto Query Language (KQL). The key construct for reaching outside the current workspace is the workspace() function, which lets you reference another Log Analytics workspace by name or resource ID—even across subscriptions or tenants when proper permissions (often via Azure Lighthouse or guest access) are in place.

Typical correlation looks like:

union workspace( ' Fabrikam-WS ' ).SecurityEvent, workspace( ' Contoso-WS ' ).SecurityEvent | …

Here, workspace() is the required element to bring together data sets from multiple tenants; operators like extend and project only shape columns and do not establish cross-tenant scope. Therefore, to meet the requirements with minimal overhead: Fabrik am needs one workspace to host its Sentinel content, and you use workspace() in your KQL to correlate Contoso and Fabrikam data.

 Table: DeviceFileEvents

 Aggregation function: count()

In Microsoft Defender XDR advanced hunting, data tables such as DeviceFileEvents , DeviceProcessEvents , and CloudAppEvents are used to investigate various types of activities. Since this query aims to investigate an issue related to file activity—specifically identifying when files have been accessed, modified, or created repeatedly—the correct data source table is DeviceFileEvents . This table contains information about file-level activities recorded by Defender for Endpoint sensors, including file path, file name, action type, and user account involved.

The KQL structure shown in the image follows standard hunting query syntax:

DeviceFileEvents

| where Timestamp > ago(2d)

| summarize activityCount = count() by FolderPath, FileName, ActionType, AccountDisplayName

| where activityCount > 5

Here’s why:

The where Timestamp > ago(2d) clause filters results from the last 2 days, a typi cal timeframe for immediate investigations.

The summarize operator groups events by FolderPath, FileName, ActionType, and AccountDisplayName, then uses count() to determine how many times each file was acted upon.

Finally, where activityCount > 5 filters t o show only unusually high-frequency activity, which might indicate suspicious or automated file manipulation.

Microsoft Defender XDR documentation highlights that DeviceFileEvents is the correct schema for file activity investigations, while DeviceProcess Events focuses on process creation and execution, and CloudAppEvents targets cloud application usage.

Thus, the verified and documented correct completions are:

Table: DeviceFileEvents

Aggregation function: count()

According to Microsoft Security Operations documentation, Microsoft Defender for Endpoint is designed to protect endpoint devices—including Windows, macOS, Android, and iOS —against cyberattacks through advanced behavioral analysis, threat intelligence, and automated investigation and remediation. In the given case study, the sales team exclusively uses iOS devices and has previously experienced attacks while exchanging files using third-party applications. These unmanaged file-sharing methods exposed the te am to malware, phishing, and data leakage threats.

By implementing Microsoft Defender for Endpoint on iOS, Contoso can apply unified endpoint protection across all mobile devices. Defender for Endpoint’s mobile threat defense (MTD) capabilities detect mali cious apps, risky network connections, jailbroken devices, and phishing attempts. It also integrates with Microsoft Intune for compliance enforcement and conditional access—ensuring only secure, compliant devices can access corporate resources. This direct ly mitigates the security challenges faced by the sales team while minimizing manual investigation effort through automated response.

Therefore, the issue affecting the sales team (mobile device attacks and unsafe file transfers) can be effectively resolve d using Microsoft Defender for Endpoint .