The Azure Suspicious Logins detection rule monitors Azure sign-in activities to identify potential unauthorized access attempts. It specifically examines login events from the SignInLogs and NonInteractiveUserSignInLogs datasets, focusing on successful logins characterized by multiple unique source IP addresses, regions, or states. The analysis is facilitated through the Splunk-based logic, which aggregates login data by user, tracking the diversity of login locations and sources to identify anomalies. The rule applies event statistics to determine if a user has logged in from various states, regions, or IP addresses, raising alerts if any of these counts exceeds one. This methodology leverages known credential-access and initial-access techniques associated with threat actors like LUCR-3, suggesting a proactive approach to combat brute force and account validation risks in Azure environments.