The 'Azure Brute Force Signin' detection rule is designed to identify potential brute force attack attempts against Azure accounts, particularly by monitoring for patterns of multiple failed login attempts followed by a successful login event. This use case leverages Azure's activity logs, focusing specifically on the `SignInLogs` and `NonInteractiveUserSignInLogs` to capture relevant authentication events. The rule analyzes login attempts, categorizing them into 'success' and 'failure' based on the action field, and counts occurrences of these outcomes over a specified time window (10 minutes). If a user has at least one successful login alongside more than two failures, this indicates potential brute force activity, triggering an alert. The detection logic uses Splunk’s search capabilities, including event grouping and multi-value counting, to streamline detection and reduce noise. This is particularly relevant for organizations using Azure Active Directory, as brute force attacks can lead to unauthorized access and credential compromise. The rule references threat actor LUCR-3, which is known for conducting such attacks, and can aid in proactive incident response efforts.