Detection rules › Splunk

Azure AD OAuth Application Consent Granted By User

Status
production
Severity
medium
Group by
Scope, aws::recipientAccountId, dest, signature, src, user, vendor_product
Author
Mauricio Velazco, Splunk
Source
github.com/splunk/security_content

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.

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.

MITRE ATT&CK coverage

TacticTechniques
Credential Access

Telemetry coverage

PlatformRecord / event type
AzureConsent to application

Rules detecting the same action

These rules filter on the same operation.

Rule body

name: Azure AD OAuth Application Consent Granted By User
id: 10ec9031-015b-4617-b453-c0c1ab729007
version: 11
creation_date: '2023-11-16'
modification_date: '2026-05-13'
author: Mauricio Velazco, Splunk
status: production
type: TTP
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.
data_source:
    - Azure Active Directory Consent to application
search: "`azure_monitor_aad` operationName=\"Consent to application\" properties.result=success | rename properties.* as * | eval permissions_index = if(mvfind('targetResources{}.modifiedProperties{}.displayName', \"ConsentAction.Permissions\") >= 0, mvfind('targetResources{}.modifiedProperties{}.displayName', \"ConsentAction.Permissions\"), -1) | eval permissions = mvindex('targetResources{}.modifiedProperties{}.newValue',permissions_index) | rex field=permissions \"Scope: (?<Scope> [ ^,]+)\" | fillnull | stats count min(_time) as firstTime max(_time) as lastTime by dest user src vendor_account vendor_product Scope signature | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `azure_ad_oauth_application_consent_granted_by_user_filter`"
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 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.
references:
    - https://attack.mitre.org/techniques/T1528/
    - https://www.microsoft.com/en-us/security/blog/2022/09/22/malicious-oauth-applications-used-to-compromise-email-servers-and-spread-spam/
    - https://learn.microsoft.com/en-us/azure/active-directory/manage-apps/protect-against-consent-phishing
    - https://learn.microsoft.com/en-us/defender-cloud-apps/investigate-risky-oauth
    - https://www.alteredsecurity.com/post/introduction-to-365-stealer
    - https://github.com/AlteredSecurity/365-Stealer
finding:
    title: User $user$ consented an OAuth application.
    entity:
        field: user
        type: user
        score: 50
analytic_story:
    - Azure Active Directory Account Takeover
asset_type: Azure Tenant
mitre_attack_id:
    - T1528
product:
    - Splunk Enterprise
    - Splunk Enterprise Security
    - Splunk Cloud
category: cloud
security_domain: identity

Stages and Predicates

Stage 1: search

`azure_monitor_aad` operationName="Consent to application" properties.result=success

Stage 2: rename

| rename properties.* as *

Stage 3: eval

| eval permissions_index = if(mvfind('targetResources{}.modifiedProperties{}.displayName', "ConsentAction.Permissions") >= 0, mvfind('targetResources{}.modifiedProperties{}.displayName', "ConsentAction.Permissions"), -1)

Stage 4: eval

| eval permissions = mvindex('targetResources{}.modifiedProperties{}.newValue',permissions_index)

Stage 5: rex

| rex field=permissions "Scope: (?<Scope> [ ^,]+)"

Stage 6: fillnull

| fillnull

Stage 7: stats

| stats count min(_time) as firstTime max(_time) as lastTime by dest user src vendor_account vendor_product Scope signature

Stage 8: search

| `security_content_ctime(firstTime)`

Stage 9: search

| `security_content_ctime(lastTime)`

Stage 10: search

| `azure_ad_oauth_application_consent_granted_by_user_filter`

Indicators

These rows show field, operator, and value matches.