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Description

The following analytic identifies the execution of the Azure Device Code Phishing attack, which can lead to Azure Account Take-Over (ATO). The detection leverages Azure AD logs specifically focusing on authentication requests to identify the attack. This technique involves creating malicious infrastructure, bypassing Multi-Factor Authentication (MFA), and bypassing Conditional Access Policies (CAPs). The attack aims to compromise users by sending them phishing emails from attacker-controlled domains and trick the victims into performing OAuth 2.0 device authentication. A successful execution of this attack can result in adversaries gaining unauthorized access to Azure AD, Exchange mailboxes, and the target's Outlook Web Application (OWA). This attack technique was detailed by security researchers including Bobby Cooke, Stephan Borosh, and others. It's crucial for organizations to be aware of this threat, as it can lead to unauthorized access and potential data breaches.

  • Type: TTP

  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

  • Last Updated: 2023-12-20
  • Author: Mauricio Velazco, Gowthamaraj Rajendran, Splunk
  • ID: d68d8732-6f7e-4ee5-a6eb-737f2b990b91

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1528 Steal Application Access Token Credential Access
T1566 Phishing Initial Access
T1566.002 Spearphishing Link Initial Access
Kill Chain Phase
  • Exploitation
  • Delivery
NIST
  • DE.CM
CIS20
  • CIS 10
CVE 


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`azure_monitor_aad` category=SignInLogs "properties.authenticationProtocol"=deviceCode 
| rename properties.* as * 
| stats count min(_time) as firstTime max(_time) as lastTime by user src_ip, appDisplayName, userAgent 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `azure_ad_device_code_authentication_filter`

Macros

The SPL above uses the following Macros:

:information_source: azure_ad_device_code_authentication_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
  • category
  • user
  • properties.authenticationProtocol
  • properties.ipAddress
  • properties.status.additionalDetails
  • properties.appDisplayName
  • properties.userAgent

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 SignInLogs log category.

Known False Positives

In most organizations, device code authentication will be used to access common Microsoft service but it may be legitimate for others. Filter as needed.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
35.0 70 50 Device code requested for $user$ from $src_ip$

: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