Detection: Azure AD Privileged Graph API Permission Assigned

Updated Date: 2024-09-30 ID: 5521f8c5-1aa3-473c-9eb7-853701924a06 Author: Mauricio Velazco, Splunk Type: TTP Product: Splunk Enterprise Security

Description

The following analytic detects the assignment of high-risk Graph API permissions in Azure AD, specifically Application.ReadWrite.All, AppRoleAssignment.ReadWrite.All, and RoleManagement.ReadWrite.Directory. It uses azure_monitor_aad data to scan AuditLogs for 'Update application' operations, identifying when these permissions are assigned. This activity is significant as it grants broad control over Azure AD, including application and directory settings. If confirmed malicious, it could lead to unauthorized modifications and potential security breaches, compromising the integrity and security of the Azure AD environment. Immediate investigation is required.

Search

1`azure_monitor_aad` category=AuditLogs operationName="Update application"  
2| eval newvalue = mvindex('properties.targetResources{}.modifiedProperties{}.newValue',0) 
3| spath input=newvalue  
4| search "{}.RequiredAppPermissions{}.EntitlementId"="1bfefb4e-e0b5-418b-a88f-73c46d2cc8e9" OR "{}.RequiredAppPermissions{}.EntitlementId"="06b708a9-e830-4db3-a914-8e69da51d44f" OR "{}.RequiredAppPermissions{}.EntitlementId"="9e3f62cf-ca93-4989-b6ce-bf83c28f9fe8"  
5| eval Permissions = '{}.RequiredAppPermissions{}.EntitlementId' 
6| stats count earliest(_time) as firstTime latest(_time) as lastTime values(Permissions) by user, object, user_agent, operationName 
7| `security_content_ctime(firstTime)` 
8| `security_content_ctime(lastTime)`   
9| `azure_ad_privileged_graph_api_permission_assigned_filter`

Data Source

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

Macros Used

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

azure_ad_privileged_graph_api_permission_assigned_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
T1003.002	Security Account Manager	Credential Access

KillChainPhase.EXPLOITAITON

NistCategory.DE_CM

Cis18Value.CIS_10

APT29

APT41

APT5

Agrius

Daggerfly

Dragonfly

Ember Bear

FIN13

GALLIUM

Ke3chang

Threat Group-3390

Wizard Spider

menuPass

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. This analytic was written to be used with the azure:monitor:aad sourcetype leveraging the AuditLog log category.

Known False Positives

Privileged Graph API permissions may be assigned for legitimate purposes. Filter as needed.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message	Risk Score	Impact	Confidence
User $user$ assigned privileged Graph API permissions to $object$	54	90	60

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: 3