This detection rule employs machine learning to identify unusual failure events in GCP Audit logs. The rule is designed to monitor for rare error codes, which may hint at attempted or successful adversarial behaviors such as privilege escalation, discovery, lateral movement, defense evasion, or persistence. The anomaly threshold is set at 50, indicating that when such errors exceed this level, the rule triggers an alert. Despite its automated nature, the potential for false positives exists, particularly given that rare and unusual failures may stem from manual troubleshooting by users, inefficiencies in cloud automation, or changes in IAM permissions. Implementing this rule requires the Elastic Agent to be configured to collect GCP Audit logs, and users must ensure the underlying machine learning job is operational. The rule is updated for production use and is currently integrated with GCP, enhancing security vigilance over cloud resource management and monitoring.