ID | Technique | Tactic |
---|---|---|
T1078 | Valid Accounts | Defense Evasion |
Detection: Azure AD Multiple AppIDs and UserAgents Authentication Spike
Description
The following analytic detects unusual authentication activity in Azure AD, specifically when a single user account has over 8 authentication attempts using 3+ unique application IDs and 5+ unique user agents within a short period. It leverages Azure AD audit logs, focusing on authentication events and using statistical thresholds. This behavior is significant as it may indicate an adversary probing for MFA requirements. If confirmed malicious, it suggests a compromised account, potentially leading to further exploitation, lateral movement, and data exfiltration. Early detection is crucial to prevent substantial harm.
Search
1`azure_monitor_aad` category=SignInLogs operationName="Sign-in activity" (properties.authenticationRequirement="multiFactorAuthentication" AND properties.status.additionalDetails="MFA required in Azure AD") OR (properties.authenticationRequirement=singleFactorAuthentication AND "properties.authenticationDetails{}.succeeded"=true)
2| bucket span=5m _time
3| rename properties.* as *
4| stats count min(_time) as firstTime max(_time) as lastTime dc(appId) as unique_app_ids dc(userAgent) as unique_user_agents values(appDisplayName) values(deviceDetail.operatingSystem) by user, src_ip
5| where count > 5 and unique_app_ids > 2 and unique_user_agents > 5
6| `security_content_ctime(firstTime)`
7| `security_content_ctime(lastTime)`
8| `azure_ad_multiple_appids_and_useragents_authentication_spike_filter`
Data Source
Name | Platform | Sourcetype | Source | Supported App |
---|---|---|---|---|
Azure Active Directory Sign-in activity | Azure | 'azure:monitor:aad' |
'Azure AD' |
N/A |
Macros Used
Name | Value |
---|---|
azure_monitor_aad | sourcetype=azure:monitor:aad |
azure_ad_multiple_appids_and_useragents_authentication_spike_filter | search * |
azure_ad_multiple_appids_and_useragents_authentication_spike_filter
is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Annotations
Default Configuration
This detection is configured by default in Splunk Enterprise Security to run with the following settings:
Setting | Value |
---|---|
Disabled | true |
Cron Schedule | 0 * * * * |
Earliest Time | -70m@m |
Latest Time | -10m@m |
Schedule Window | auto |
Creates Risk Event | True |
Implementation
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 through an EventHub. This analytic was written to be used with the azure:monitor:aad sourcetype leveraging the SignInLogs log category.
Known False Positives
Rapid authentication from the same user using more than 5 different user agents and 3 application IDs is highly unlikely under normal circumstances. However, there are potential scenarios that could lead to false positives.
Associated Analytic Story
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
$user$ authenticated in a short periof of time with more than 5 different user agents across 3 or more unique application ids. | 48 | 60 | 80 |
References
Detection Testing
Test Type | Status | Dataset | Source | Sourcetype |
---|---|---|---|---|
Validation | ✅ Passing | N/A | N/A | N/A |
Unit | ✅ Passing | Dataset | Azure AD |
azure:monitor:aad |
Integration | ✅ Passing | Dataset | Azure AD |
azure:monitor:aad |
Replay any dataset to Splunk Enterprise by using our replay.py
tool or the UI.
Alternatively you can replay a dataset into a Splunk Attack Range
Source: GitHub | Version: 4