The rule 'Unusual Hour for a User to Logon' leverages a machine learning job to identify when a user logs in at atypical times. The logic behind this detection centers on the premise that a user may be logging in due to compromised credentials if the user and the threat actor are in different time zones. Furthermore, unauthorized activities tend to occur during non-business hours, making this rule critical for identifying potential security breaches. The rule outlines the use of anomaly detection thresholds set at 75, indicating a moderate level of confidence in the detection. It also provides guidelines for setting up necessary integrations, including Elastic Defend and Auditd Manager, which are required to gather relevant data for accurate detections. Investigative procedures and response actions are also embedded within the rule, emphasizing the need to assess user behavior and confirm any suspicious activities with the user in question.