Detection: Azure AD Block User Consent For Risky Apps Disabled

Updated Date: 2024-09-30 ID: 875de3d7-09bc-4916-8c0a-0929f4ced3d8 Author: Mauricio Velazco, Splunk Type: TTP Product: Splunk Enterprise Security

Description

The following analytic detects when the risk-based step-up consent security setting in Azure AD is disabled. It monitors Azure Active Directory logs for the "Update authorization policy" operation, specifically changes to the "AllowUserConsentForRiskyApps" setting. This activity is significant because disabling this feature can expose the organization to OAuth phishing threats by allowing users to grant consent to potentially malicious applications. If confirmed malicious, attackers could gain unauthorized access to user data and sensitive information, leading to data breaches and further compromise within the organization.

Search

 1`azure_monitor_aad` operationName="Update authorization policy" 
 2| rename properties.* as *  
 3| eval index_number = if(mvfind('targetResources{}.modifiedProperties{}.displayName', "AllowUserConsentForRiskyApps") >= 0, mvfind('targetResources{}.modifiedProperties{}.displayName', "AllowUserConsentForRiskyApps"), -1) 
 4| search index_number >= 0  
 5| eval AllowUserConsentForRiskyApps = mvindex('targetResources{}.modifiedProperties{}.newValue',index_number) 
 6| search AllowUserConsentForRiskyApps = "[true]" 
 7| stats count min(_time) as firstTime max(_time) as lastTime by user, src_ip, operationName, AllowUserConsentForRiskyApps 
 8| `security_content_ctime(firstTime)` 
 9| `security_content_ctime(lastTime)` 
10| `azure_ad_block_user_consent_for_risky_apps_disabled_filter`

Data Source

Name	Platform	Sourcetype	Source
Azure Active Directory Update authorization policy	Azure	`'azure:monitor:aad'`	`'Azure AD'`

Macros Used

Name	Value
azure_monitor_aad	`sourcetype=azure:monitor:aad`
azure_ad_block_user_consent_for_risky_apps_disabled_filter	`search *`

azure_ad_block_user_consent_for_risky_apps_disabled_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
T1562	Impair Defenses	Defense Evasion

KillChainPhase.EXPLOITAITON

NistCategory.DE_CM

Cis18Value.CIS_10

Magic Hound

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

This configuration file applies to all detections of type TTP. These detections will use Risk Based Alerting and generate Notable Events.

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

Legitimate changes to the 'risk-based step-up consent' setting by administrators, perhaps as part of a policy update or security assessment, may trigger this alert, necessitating verification of the change's intent and authorization

Associated Analytic Story

Azure Active Directory Account Takeover

Risk Based Analytics (RBA)

Risk Message	Risk Score	Impact	Confidence
User $user$ disabled the BlockUserConsentForRiskyApps Azure AD setting.	30	60	50

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

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