Try in Splunk Security Cloud

Description

This analytic detects when the risk-based step-up consent security setting in Azure AD is disabled. This setting, when enabled, prevents regular users from granting consent to potentially malicious OAuth applications, requiring an administrative step-up for consent instead. Disabling this feature could expose the organization to OAuth phishing threats.The detection operates by monitoring Azure Active Directory logs for events where the "Update authorization policy" operation is performed. It specifically looks for changes to the "AllowUserConsentForRiskyApps" setting, identifying instances where this setting is switched to "true," effectively disabling the risk-based step-up consent. Monitoring for changes to critical security settings like the "risk-based step-up consent" is vital for maintaining the integrity of an organization's security posture. Disabling this feature can make the environment more susceptible to OAuth phishing attacks, where attackers trick users into granting permissions to malicious applications. Identifying when this setting is disabled can help blue teams to quickly respond, investigate, and potentially uncover targeted phishing campaigns against their users. If an attacker successfully disables the "risk-based step-up consent" and subsequently launches an OAuth phishing campaign, they could gain unauthorized access to user data and other sensitive information within the M365 environment. This could lead to data breaches, unauthorized access to emails, and potentially further compromise within the organization

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Risk
  • Last Updated: 2023-12-20
  • Author: Mauricio Velazco, Splunk
  • ID: 875de3d7-09bc-4916-8c0a-0929f4ced3d8

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1562 Impair Defenses Defense Evasion
Kill Chain Phase
  • Exploitation
NIST
  • DE.CM
CIS20
  • CIS 10
CVE 


1
2
3
4
5
6
7
8
9
10



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

Macros

The SPL above uses the following Macros:

:information_source: azure_ad_block_user_consent_for_risky_apps_disabled_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.targetResources{}.modifiedProperties{}.displayName
  • properties.targetResources{}.modifiedProperties{}.newValue
  • user
  • src_ip

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

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

RBA

Risk Score Impact Confidence Message
30.0 60 50 User $user$ disabled the BlockUserConsentForRiskyApps Azure AD setting.

: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.

Reference

Test Dataset

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 | version: 2