ID | Technique | Tactic |
---|---|---|
T1528 | Steal Application Access Token | Credential Access |
Detection: Azure AD OAuth Application Consent Granted By User
Description
The following analytic detects when a user in an Azure AD environment grants consent to an OAuth application. It leverages Azure AD audit logs to identify events where users approve application consents. This activity is significant as it can expose organizational data to third-party applications, a common tactic used by malicious actors to gain unauthorized access. If confirmed malicious, this could lead to unauthorized access to sensitive information and resources. Immediate investigation is required to validate the application's legitimacy, review permissions, and mitigate potential risks.
Search
1`azure_monitor_aad` operationName="Consent to application" properties.result=success
2| rename properties.* as *
3| eval permissions_index = if(mvfind('targetResources{}.modifiedProperties{}.displayName', "ConsentAction.Permissions") >= 0, mvfind('targetResources{}.modifiedProperties{}.displayName', "ConsentAction.Permissions"), -1)
4| eval permissions = mvindex('targetResources{}.modifiedProperties{}.newValue',permissions_index)
5| rex field=permissions "Scope: (?<Scope>[^,]+)"
6| stats count min(_time) as firstTime max(_time) as lastTime by operationName, user, Scope
7| `security_content_ctime(firstTime)`
8| `security_content_ctime(lastTime)`
9| `azure_ad_oauth_application_consent_granted_by_user_filter`
Data Source
Name | Platform | Sourcetype | Source | Supported App |
---|---|---|---|---|
Azure Active Directory Consent to application | Azure | 'azure:monitor:aad' |
'Azure AD' |
N/A |
Macros Used
Name | Value |
---|---|
azure_monitor_aad | sourcetype=azure:monitor:aad |
azure_ad_oauth_application_consent_granted_by_user_filter | search * |
azure_ad_oauth_application_consent_granted_by_user_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 Notable | Yes |
Rule Title | %name% |
Rule Description | %description% |
Notable Event Fields | user, dest |
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 AuditLog log category.
Known False Positives
False positives may occur if users are granting consents as part of legitimate application integrations or setups. It is crucial to review the application and the permissions it requests to ensure they align with organizational policies and security best practices.
Associated Analytic Story
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
User $user$ consented an OAuth application. | 36 | 60 | 60 |
References
-
https://learn.microsoft.com/en-us/defender-cloud-apps/investigate-risky-oauth
-
https://www.alteredsecurity.com/post/introduction-to-365-stealer
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: 3