This detection rule is designed to identify unusual processes running on Windows hosts, which might indicate unauthorized services, malware activity, or persistence mechanisms. It utilizes machine learning to detect processes that are rarely executed on individual hosts, suggesting anomalous behavior. The rule leverages various Osquery commands to gather data about the system's processes, service accounts, and DNS cache, facilitating comprehensive investigations of rare process activities. False positives may arise from newly installed software or infrequent legitimate workflows, necessitating careful analysis of the process execution chain and user context. Successful implementation requires integration with Elastic Defend and relevant machine learning jobs, ensuring a continuous anomaly detection process on Windows systems. The rule operates with a low-risk score, but given its capability to identify potentially malicious activities, thorough triage and incident response protocols are essential.