According to the Microsoft SC-300: Identity and Access Administrator Study Guide and the Microsoft Learn module “Monitor and respond to Azure AD events with Azure Sentinel”, multi-staged attacks are advanced threat scenarios that require correlation of multiple events — for example, a suspicious sign-in followed by abnormal Office 365 activity.
The scenario in the question states:
“Litware wants to use the Fusion rule in Azure Sentinel to detect multi-staged attacks that include a combination of suspicious Azure AD sign-ins followed by anomalous Microsoft Office 365 activity.”
Azure Sentinel’s Fusion rule is a built-in, machine-learning–driven correlation rule that automatically detects multi-stage attacks by analyzing anomalies across multiple data sources such as Azure AD sign-in logs, Office 365 activity, and security alerts.
However, to fine-tune detection or meet specific organizational monitoring requirements, administrators can customize the rule logic in Sentinel analytics. This allows you to define how different signals and events are correlated, what thresholds trigger an alert, and how Sentinel interprets combined anomalies.
Microsoft documentation states:
“Fusion uses correlation logic in analytics rules to detect complex multi-stage attacks. Administrators can customize rule logic to meet specific detection requirements and fine-tune alert sensitivity.”
The other options do not meet the requirement:
B. Create a workbook → Used for visualization and reporting, not detection.
C. Add data connectors → Used to ingest data sources; this is already configured.
D. Add a playbook → Used for automated response, not for detection logic configuration.
✅ Correct Answer: A. Customize the Azure Sentinel rule logic