Microsoft Microsoft Security Operations Analyst SC-200 Exam Dumps: Updated Questions & Answers (November 2025)

When connecting an Amazon Web Services (AWS) account to Microsoft Defender for Cloud using the native cloud connector, the very first requirement is to allow Defender for Cloud to access AWS resources securely. According to official Microsoft Defender for Cloud documentation, this is accomplished by creating an AWS Identity and Access Management (IAM) role that grants Microsoft Defender for Cloud the necessary permissions to read configuration and security data from the AWS environment.

Here’s the detailed process based on Microsoft documentation:

1️⃣ Create an IAM Role in AWS:

In the AWS console, you create an IAM role that establishes a trust relationship with Microsoft Defender for Cloud’s AWS connector. The trust policy allows Azure’s Defender for Cloud service principal to assume the role securely.

2️⃣ Attach the Required Policies:

The IAM role is then granted read-only permissions by attaching the Microsoft-provided policy template. This policy enables Defender for Cloud to assess AWS resources, collect security configuration data, and generate security recommendations.

3️⃣ Connect the AWS Account in Defender for Cloud:

After the IAM role is in place, you return to Azure and complete the connector setup by providing the Role ARN (Amazon Resource Name). Defender for Cloud then uses this role to continuously monitor and assess the AWS environment.

Options such as creating an AWS user or configuring AWS Security Hub are subsequent integration or enhancement steps, not the first action in setting up the native connector. Deploying the SSM agent is only required for enabling Defender for Servers on AWS EC2 instances, not for the initial connector setup.

✅ Therefore, the correct answer is B. Create an Access control (IAM) role for Defender for Cloud.

For a near-real-time (NRT) analytics rule that detects sign-ins by a designated break-glass account, the most direct and performant pattern is to filter SigninLogs by joining to a Microsoft Sentinel watchlist that contains the protected account(s). Sentinel exposes watchlists to KQL through the helper function _GetWatchlist('<watchlist-name>'), which returns a table with standard columns (including SearchKey) plus any custom columns you imported. Using join kind=inner ensures the result set includes only those SigninLogs rows whose UserPrincipalName matches an entry in the watchlist—ideal for alerting on a high-value account without post-filtering.

The completed query is:

SigninLogs | join kind=inner (_GetWatchlist('breakglass_account')) on $left.UserPrincipalName == $right.SearchKey

This approach satisfies the requirement to implement an NRT rule for the break-glass account because:

NRT rules support KQL with joins and watchlists and are optimized for rapid evaluation over fresh data.

Using a watchlist lets SecOps adjust monitored accounts without editing the rule—minimizing administrative effort and aligning with least-privilege operations (no extra permissions beyond watchlist management).

The inner join pattern reduces noise by returning only matched events, which are then turned into alerts/incidents by the NRT rule.

Thus, select join and GetWatchlist, and join UserPrincipalName to the watchlist’s SearchKey.

msticpy is a library for InfoSec investigation and hunting in Jupyter Notebooks. It includes functionality to: query log data from multiple sources. enrich the data with Threat Intelligence, geolocations and Azure resource data. extract Indicators of Activity (IoA) from logs and unpack encoded data.

MSTICPy reduces the amount of code that customers need to write for Microsoft Sentinel, and provides:

Data query capabilities, against Microsoft Sentinel tables, Microsoft Defender for Endpoint, Splunk, and other data sources.

Threat intelligence lookups with TI providers, such as VirusTotal and AlienVault OTX.

Enrichment functions like geolocation of IP addresses, Indicator of Compromise (IoC) extraction, and WhoIs lookups.

Visualization tools using event timelines, process trees, and geo mapping.

Advanced analyses, such as time series decomposition, anomaly detection, and clustering.

To ingest security logs from Linux virtual machines into Microsoft Sentinel efficiently, Microsoft recommends using the Common Event Format (CEF) connector.

The CEF connector allows Linux machines to send logs in a structured, normalized format via Syslog, minimizing custom parsing in Sentinel. The CEF schema is widely adopted by SIEM and security products, ensuring compatibility and simplified analytics rule creation.

How it works:

The Linux VMs send logs to a local Syslog daemon.

The Syslog daemon forwards the logs (in CEF format) to the Log Analytics workspace connected to Microsoft Sentinel.

Sentinel automatically maps CEF fields, minimizing parsing and normalization effort.

Why not the others:

REST API integration: Requires custom scripting and parsing — high admin effort.

Syslog connector: Sends raw logs that need additional parsing and normalization.

Log Analytics Data Collector API: Used for custom ingestion scenarios, not scalable for 100 VMs.

✅ Correct Answer: D. a Common Event Format (CEF) connector

The Sentinel requirement states:

“Ensure that multiple alerts generated by rulequery1 in response to a single user launching Azure Cloud Shell multiple times are consolidated as a single incident.”

This behavior is controlled by the event grouping setting in the analytics rule configuration.

Microsoft Sentinel documentation explains:

“Event grouping determines how alerts generated from the same rule are grouped into incidents. Selecting ‘Group all alerts triggered by this rule into a single incident’ allows all related alerts to be combined.”

Hence, configuring event grouping ensures that all alerts from rulequery1 related to the same user are consolidated into one incident, satisfying the requirement.

✅ Answer for Question 10: C. event grouping

In Microsoft Sentinel’s Advanced Security Information Model (ASIM), DNS queries are normalized through the Im_Dns parser, which unifies DNS telemetry from multiple sources (Infoblox, Windows DNS, Azure Firewall DNS proxy, etc.). Microsoft guidance states that when you need broad compatibility and want to “use built-in ASIM parsers whenever possible,” you should call the generic Im_Dns() parser. To minimize overhead, ASIM provides a pack parameter that restricts the parser to a specific content pack (vendor/source) so it won’t iterate through all available source parsers under the hood. For Infoblox NIOS, you pass the Infoblox pack via the pack parameter, which limits parsing to the Infoblox implementation and reduces query cost/latency while keeping the query portable across environments.

Putting it together, the recommended pattern is:

Im_Dns(pack="InfobloxNIOS")

| where DnsResponseCodeName == "NXDOMAIN"

| summarize count()

This approach satisfies all requirements:

Uses built-in ASIM (Im_Dns).

Minimizes query overhead (uses pack to limit parsing to Infoblox).

Targets NXDOMAIN responses for counting DNS request failures from Infoblox1.

To have a Microsoft Sentinel workbook pull live data from an external web service, you use the workbook’s built-in JSON data source. Workbooks can query REST endpoints that return JSON and render results dynamically in visuals. Because the Azure portal (where the workbook runs) is a different origin than your on-prem/public Webapp1, browsers will block these cross-origin requests unless the endpoint explicitly allows them. Therefore, the external service must enable CORS to permit the portal’s origin to fetch the JSON. This aligns with Microsoft guidance that Workbooks can query HTTP/HTTPS JSON endpoints and that external endpoints must allow cross-origin requests for client-side calls from the Azure portal. Enforcing CORS on Webapp1 satisfies the security model while enabling the workbook to retrieve data at view time—meeting the requirement to “dynamically retrieve data from Webapp1.” Options like “custom endpoint” or “custom resource provider” aren’t needed here, and enabling SOP or only enforcing TLS 1.2 wouldn’t address the browser’s cross-origin policy blocking the call.

To monitor and detect higher-than-normal volumes of password resets, you need to gather password reset event data both from Azure Active Directory (cloud identities) and from on-premises Active Directory (domain accounts). Microsoft’s official Defender XDR and Sentinel integration guidance describes that:

Azure AD Password Protection enforces and monitors password policies in both cloud and hybrid environments. It can detect weak, commonly used, or compromised passwords and logs related password change/reset activities. Deploying Azure AD Password Protection extends password reset visibility to on-premises domain controllers through the Password Protection proxy and DC agent. This makes it the correct choice for implementing monitoring at the identity environment level.

In Microsoft Sentinel, to ingest and analyze password reset activities from on-premises servers (e.g., domain controllers), you must use the Windows Security Events via AMA connector. This connector collects Event ID 4723 (password change), 4724 (password reset), and related security logs directly from Windows Servers into the Sentinel Log Analytics workspace through the Azure Monitor Agent (AMA). Once the events are available in Sentinel, they can be correlated with other identity or behavioral analytics to detect abnormal reset volumes or potential compromise attempts.

The other options are not suitable:

Microsoft Defender for Identity focuses on identity compromise detection, not specifically on password reset volume monitoring.

Smart lockout protects against brute-force sign-in attempts but doesn’t generate detailed reset event telemetry.

Microsoft security rule and UEBA are higher-level analytic configurations, not data ingestion mechanisms.

Therefore, to meet the Sentinel requirements for monitoring password reset anomalies:

✅ Implement in the identity environment: Azure AD Password Protection

✅ Configure in Microsoft Sentinel: The Windows Security Events via AMA connector

The requirement is to enable Microsoft Defender for Servers Plan 2 on all Azure VMs while excluding Server2 from agentless scanning. Defender for Cloud provides a built-in mechanism to exclude specific machines from agentless scanning based on resource tags. The process is: assign a distinct tag name:value to the VM you want to exclude (Server2), and then, in Defender for Cloud’s Agentless scanning for machines settings, specify that tag pair under exclusions. Defender’s continuous discovery honors these exclusions and skips any VM that matches the configured tag. This approach aligns with the business requirement of least privilege and minimal administrative effort: it avoids broad configuration changes, requires no extensions on the VM, and is reversible by simply removing or changing the tag. The Microsoft Antimalware extension and Automanage configuration are unrelated to agentless scanning behavior, and a resource lock would only prevent modifications/deletions, not scanning. Therefore, to meet the Defender for Cloud requirement precisely, configure an Azure resource tag on Server2 and reference that tag in the agentless scanning exclusion settings.

To monitor Windows Security events from Server1 using the Windows Security Events via AMA connector, the first object you must create is a Data Collection Rule (DCR). With the Azure Monitor Agent (AMA) model used by Microsoft Sentinel, data flow is controlled by DCRs, not by the legacy MMA/OMS workspace settings. A DCR defines what to collect (e.g., the Security event log, specific event IDs or XPath queries), from where (the target machines or machine groups), and where to send it (the Sentinel/Log Analytics workspace). After creating the DCR, you associate it with Server1 (Arc-enabled), and the connector will begin streaming Security events to your Sentinel workspace. Creating a Sentinel scheduled rule or an automation rule does not enable collection; those features act after data is already ingested. Event Grid topics are unrelated to Windows event collection. Therefore, the correct first step for meeting the Sentinel requirement to monitor Server1’s Security log via AMA is to create a DCR, then assign it to Server1 and the Sentinel workspace.