The detection rule 'Unusual Process For a Linux Host' leverages machine learning to identify rare processes occurring on Linux hosts that deviate from established execution patterns. It flags these anomalies when processes are found running that previously have not been observed frequently, which can indicate potentially unauthorized services, malware, or circumstantial evidence of persistence mechanisms employed by attackers. To function properly, the rule requires integration with either the Elastic Defend or Auditd Manager systems, along with the associated machine learning job. The rule operates by examining process execution records and comparing them against a baseline of typical activity for the respective host. Risks of false positives exist, particularly for new applications or those that fit rare execution patterns due to legitimate monthly or quarterly tasks. Guidance for investigation and response is provided, emphasizing the need for contextual analysis pertaining to user activities, and if necessary, implementing incident response protocols to handle potential threats as identified through the alerts. The rule has a risk score of 21 and is categorized under 'low' severity, primarily focusing on detecting unsolicited modifications to system processes. Refer to the MITRE ATT&CK framework for related techniques, specifically under the tactic of persistence.