This detection rule utilizes machine learning to identify abnormal spikes in user lifecycle management change events within Okta, which may indicate potential privilege escalation activities. It monitors for unusual patterns in user account modifications, as malicious actors can exploit user accounts to gain elevated access rights or maintain persistence in compromised environments. The rule is configured to trigger alerts when the anomaly detection threshold reaches 75, reflecting a significant deviation from normal behavioral patterns. This reinforces proactive security measures by enabling early detection of potential malicious activities.