The rule identifies high-risk sign-ins in Azure Active Directory by leveraging the machine learning capabilities and heuristics of Microsoft Identity Protection. It triggers on events where the risk state is identified as 'confirmedCompromised' or 'atRisk', coupled with a successful sign-in event. This detection aims to alert security teams of suspicious activity that may indicate compromised user accounts. The rule relies on data collected from Azure sign-in logs and requires the integration of Azure Fleet or similar data structures to function effectively. Investigative steps include checking the risk detection type, validating user activity, examining associated alerts, and assessing the overall impact while following incident response protocols. It highlights the importance of disabling or limiting accounts during an investigation, ensuring compliance with change management procedures, and maintaining security best practices, including MFA and regular audits.