The following analytic triggers on a high risk sign-in against Azure Active Directory identified by Azure Identity Protection. Identity Protection monitors sign-in events using heuristics and machine learning to identify potentially malicious events and categorizes them in three categories high, medium and low.
- Type: TTP
Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Last Updated: 2022-07-11
- Author: Mauricio Velazco, Splunk
- ID: 1ecff169-26d7-4161-9a7b-2ac4c8e61bea
Kill Chain Phase
- CIS 3
- CIS 5
- CIS 16
1 2 3 4 `azuread` body.category=UserRiskEvents body.properties.riskLevel=high | rename body.properties.* as * | stats values(userPrincipalName) by _time, ipAddress, activity, riskLevel, riskEventType, additionalInfo | `azure_active_directory_high_risk_sign_in_filter`
The SPL above uses the following Macros:
azure_active_directory_high_risk_sign-in_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
List of fields required to use this analytic.
How To Implement
You must install the latest version of Splunk Add-on for Microsoft Cloud Services from Splunkbase (https://splunkbase.splunk.com/app/3110/#/details). You must be ingesting Azure Active Directory events into your Splunk environment. You must be ingesting Azure Active Directory events in your Splunk environment. Specifically, this analytic leverages the RiskyUsers and UserRiskEvents log category.
Known False Positives
Details for the risk calculation algorithm used by Identity Protection are unknown and may be prone to false positives.
Associated Analytic Story
|54.0||60||90||A high risk event was identified by Identify Protection for user $body.properties.userPrincipalName$|
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
source | version: 1