Detection: Azure AD Device Code Authentication

Updated Date: 2024-05-28 ID: d68d8732-6f7e-4ee5-a6eb-737f2b990b91 Author: Mauricio Velazco, Gowthamaraj Rajendran, Splunk Type: TTP Product: Splunk Enterprise Security

Description

The following analytic identifies Azure Device Code Phishing attacks, which can lead to Azure Account Take-Over (ATO). It leverages Azure AD SignInLogs to detect suspicious authentication requests using the device code authentication protocol. This activity is significant as it indicates potential bypassing of Multi-Factor Authentication (MFA) and Conditional Access Policies (CAPs) through phishing emails. If confirmed malicious, attackers could gain unauthorized access to Azure AD, Exchange mailboxes, and Outlook Web Application (OWA), leading to potential data breaches and unauthorized data access.

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

Data Source

Name Platform Sourcetype Source Supported App
Azure Active Directory Azure icon Azure 'azure:monitor:aad' 'Azure AD' N/A

Macros Used

Name Value
azure_monitor_aad sourcetype=azure:monitor:aad
azure_ad_device_code_authentication_filter search *
azure_ad_device_code_authentication_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
T1528 Steal Application Access Token Credential Access
T1566 Phishing Initial Access
T1566.002 Spearphishing Link Initial Access
KillChainPhase.DELIVERY
KillChainPhase.EXPLOITAITON
NistCategory.DE_CM
Cis18Value.CIS_10
APT28
APT29
Axiom
GOLD SOUTHFIELD
APT1
APT28
APT29
APT3
APT32
APT33
APT39
BlackTech
Cobalt Group
Confucius
EXOTIC LILY
Earth Lusca
Elderwood
Ember Bear
Evilnum
FIN4
FIN7
FIN8
Kimsuky
Lazarus Group
LazyScripter
Leviathan
LuminousMoth
Machete
Magic Hound
Mofang
Molerats
MuddyWater
Mustang Panda
Mustard Tempest
OilRig
Patchwork
Sandworm Team
Sidewinder
TA2541
TA505
Transparent Tribe
Turla
Windshift
Wizard Spider
ZIRCONIUM

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 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

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
Device code requested for $user$ from $src_ip$ 35 70 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: 3