The rule 'Potential Data Exfiltration Activity to an Unusual Region' employs machine learning to identify potential data exfiltration to atypical geographic regions. This detection is based on analyzing data transfers that deviate from established traffic patterns for an organization, potentially indicating malicious activities such as command-and-control operations by adversaries. The rule requires the Data Exfiltration Detection integration, which relies on network and file event data, collected via the Elastic Defend and Network Packet Capture integrations. Administrators must ensure the appropriate setup and prerequisite requirements are met to enable effective anomaly detection. The detection employs thresholds defined by the machine learning job to flag any significant deviations, which are scored at a low risk but warrant investigation based on the geo-location of the data transfer. Detailed steps for setup, investigation, and remediation are provided to facilitate a structured approach to analyzing flagged alerts and responding to potential threats or false positives.