This rule is designed to detect potential data exfiltration activity through the use of machine learning, with a particular focus on identifying unusual data transfers to specific geo-locations based on IP addresses. The detection mechanic leverages an anomaly detection model to analyze network and file event patterns, specifically flagging any anomalies that exceed a defined threshold (75 in this case). If the system detects elevated data transmissions to atypical destinations that do not match the organization's historical patterns, an alert will trigger, potentially indicating malicious activities such as command and control (C2) operations by threat actors. The rule functions within a framework of data exfiltration detection, requiring various integrations and event collections for optimal performance, including Elastic Defend and Network Packet Capture integrations. It operates every 15 minutes, assessing network traffic over the previous six hours to identify any indicators of compromise. Investigative avenues suggested by the detection include examining the specific geo-locations and IP addresses flagged by alerts, cross-referencing them against known threat intelligence, and reviewing past network logs for potential links to these addresses.