This rule, titled 'Spike in Special Privilege Use Events', leverages machine learning to detect anomalous increases in special privilege usage, which could indicate unauthorized access or privilege escalation attempts. The rule is targeted at environments with Windows operating systems utilizing the Privileged Access Detection (PAD) integration. It operates by continuously monitoring usage events for signs of irregular activity over a rolling 3-hour window and assesses these events in 15-minute intervals. A risk score of 21 indicates the potential severity of detected anomalies. The detection mechanism primarily uses Elastic's machine learning capabilities to identify unusual spikes, flagging them for investigation to determine if they correspond to unauthorized tasks being executed within the system. The implementation requires the collection of Windows logs and specific integrations such as Elastic Defend. Investigative guidance is provided to assess potential misuse, including reviewing user behavior against operational norms and responding to any detected incidents decisively, thereby helping maintain system integrity.