Detection: Azure AD Multiple AppIDs and UserAgents Authentication Spike

Updated Date: 2024-11-14 ID: 5d8bb1f0-f65a-4b4e-af2e-fcdb88276314 Author: Mauricio Velazco, Splunk Type: Anomaly Product: Splunk Enterprise Security

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" properties.status.additionalDetails="MFA required in Azure AD") OR (properties.authenticationRequirement=singleFactorAuthentication "properties.authenticationDetails{}.succeeded"=true) 
 2| bucket span=5m _time 
 3| rename properties.* as * 
 4| rename userAgent as user_agent 
 5| fillnull 
 6| stats count dc(appId) as unique_app_ids dc(user_agent) as unique_user_agents min(_time) as firstTime max(_time) as lastTime values(dest) as dest values(user_agent) as user_agent by user src vendor_account vendor_product signature 
 7| where count > 5 and unique_app_ids > 2 and unique_user_agents > 5 
 8| `security_content_ctime(firstTime)` 
 9| `security_content_ctime(lastTime)` 
10| `azure_ad_multiple_appids_and_useragents_authentication_spike_filter`

Data Source

Name	Platform	Sourcetype	Source
Azure Active Directory Sign-in activity	Azure	`'azure:monitor:aad'`	`'Azure AD'`

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

- MITRE ATT&CK

+ Kill Chain Phases

+ NIST

+ CIS

- Threat Actors

ID	Technique	Tactic
T1078	Valid Accounts	Defense Evasion

Delivery

Exploitation

Installation

DE.AE

CIS 10

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

This configuration file applies to all detections of type anomaly. These detections will use Risk Based Alerting.

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

Azure Active Directory Account Takeover

Risk Based Analytics (RBA)

Risk Message:

$user$ authenticated in a short periof of time with more than 5 different user agents across 3 or more unique application ids.

Risk Object	Risk Object Type	Risk Score	Threat Objects
user	user	48	No Threat Objects

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: 9