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The following analytic identifies instances where Azure AD has blocked a user's attempt to grant consent to an application deemed risky or potentially malicious. This suggests that the application has exhibited behaviors or characteristics that are commonly associated with malicious intent or poses a security risk. This detection leverages the Azure AD audit logs, specifically focusing on events related to user consent actions and system-driven blocks. By filtering for blocked consent actions associated with applications, the analytic highlights instances where Azure's built-in security measures have intervened. Applications that are flagged and blocked by Azure typically exhibit suspicious characteristics or behaviors. Monitoring for these blocked consent attempts helps security teams identify potential threats early on and can provide insights into users who might be targeted or susceptible to such risky applications. It's an essential layer of defense in ensuring that malicious or risky applications don't gain access to organizational data. If the detection is a true positive, it indicates that the built-in security measures of O365 successfully prevented a potentially harmful application from gaining access. However, the attempt itself suggests that either a user might be targeted or that there's a presence of malicious applications trying to infiltrate the organization. Immediate investigation is required to understand the context of the block and to take further preventive measures.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Risk
  • Last Updated: 2023-10-27
  • Author: Mauricio Velazco, Splunk
  • ID: 06b8ec9a-d3b5-4882-8f16-04b4d10f5eab




ID Technique Tactic
T1528 Steal Application Access Token Credential Access
Kill Chain Phase
  • Exploitation
  • DE.CM
  • CIS 10
`azure_monitor_aad` operationName="Consent to application" properties.result=failure 
| rename properties.* as *  
| eval reason_index = if(mvfind('targetResources{}.modifiedProperties{}.displayName', "ConsentAction.Reason") >= 0, mvfind('targetResources{}.modifiedProperties{}.displayName', "ConsentAction.Reason"), -1) 
| eval permissions_index = if(mvfind('targetResources{}.modifiedProperties{}.displayName', "ConsentAction.Permissions") >= 0, mvfind('targetResources{}.modifiedProperties{}.displayName', "ConsentAction.Permissions"), -1) 
| search reason_index >= 0  
| eval reason = mvindex('targetResources{}.modifiedProperties{}.newValue',reason_index) 
| eval permissions = mvindex('targetResources{}.modifiedProperties{}.newValue',permissions_index) 
| search reason = "\"Risky application detected\"" 
| rex field=permissions "Scope: (?<Scope>[^,]+)" 
| stats count min(_time) as firstTime max(_time) as lastTime by operationName, user, reason, Scope 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `azure_ad_user_consent_blocked_for_risky_application_filter`


The SPL above uses the following Macros:

:information_source: azure_ad_user_consent_blocked_for_risky_application_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

  • _time
  • operationName
  • properties.result
  • properties.targetResources{}.modifiedProperties{}.displayName
  • properties.targetResources{}.modifiedProperties{}.newValue

How To Implement

You must install the latest version of Splunk Add-on for Microsoft Cloud Services from Splunkbase ( 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


Associated Analytic Story


Risk Score Impact Confidence Message
30.0 30 100 Azure AD has blocked $user$ attempt to grant to consent to an application deemed risky.

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.


Test Dataset

Replay any dataset to Splunk Enterprise by using our tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range

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