The rule leverages a supervised machine learning model called ProblemChild to flag suspicious Windows process events that have a high probability of being malicious. This is achieved through examining patterns and probabilities associated with Windows processes, where events with a prediction probability exceeding 0.98 or those listed in a blocklist are identified as potential threats. The setup requires the Living off the Land (LotL) Attack Detection integration assets, and Windows process events must be collected from components like Elastic Defend or Winlogbeat. To mitigate false positives, particular benign patterns, such as files generated by Nessus scans in the Windows temp directory, are excluded from detection. This rule aims to enhance the security posture against defense evasion tactics by identifying processes that could be used for malicious activities while providing a structured investigation and remediation approach.