Detection: Azure AD Suspicious Device Registration

Created: 2026-10-12 Last Updated: 2026-10-12 ID: 4cfe7afd-a22b-4af5-9520-39f7f6564e7f Author: Jake Enea, Onur Mustafa Erdogan, Splunk Type: Anomaly Product: Splunk Enterprise Security

Description

The following analytic detects suspicious Azure Active Directory device registrations by monitoring "Register device" audit events for device names matching specific DESKTOP patterns or the user agent "Dsreg/10.0 (Windows 10.0.19041.928)". This user agent may indicate device registration activity through ROADtools, an offensive security framework targeting EntraID deployments. Device registration can support persistence or provide a device identity that can be used to access internal resources. If confirmed malicious, an attacker could use the registered device to maintain access or facilitate further compromise of the environment.

Search

 1`azure_monitor_aad` operationName="Register device" (
 2    properties.targetResources{}.displayName IN (
 3        "*-PC",
 4        "DESKTOP-*",
 5        "EC2AMAZ-*",
 6        "LAPTOP-*",
 7        "MININT-*",
 8        "MSEDGEWIN10",
 9        "WIN-*"
10    )
11    OR
12    properties.userAgent="Dsreg/*"
13)
14
15| rename properties.targetResources{}.displayName as dvc, properties.userAgent as user_agent
16
17| fillnull
18
19| stats count min(_time) as firstTime
20              max(_time) as lastTime
21              values(result) as result
22              values(user_agent) as user_agent
23
24  by tenantId user src dvc signature vendor_account vendor_product
25
26
27| `security_content_ctime(firstTime)` 
28| `security_content_ctime(lastTime)` 
29| `azure_ad_suspicious_device_registration_filter`

Data Source

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

Macros Used

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

azure_ad_suspicious_device_registration_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
T1098.005	Device Registration	Persistence
T1586.003	Cloud Accounts	Privilege Escalation

Exploitation

Weaponization

Installation

DE.AE

CIS 10

APT29

APT41

Scattered Spider

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 Finding (Notable)	No
Creates Intermediate Finding (Risk Event)	Yes

Anomaly detections generate Intermediate Findings (Risk Events). They do not generate a Finding (Notable) directly.

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

Users may register devices with names that match the suspicious patterns. Filter as needed.

Associated Analytic Story

Intermediate Findings

Message	Entity Field	Entity Type	Risk Score
Suspicious device was registered for [$user$] from [$src$] using device name [$dvc$].	src	system	20
Suspicious device was registered for [$user$] from [$src$] using device name [$dvc$].	user	user	20

Threat Objects

Field	Type
src	ip_address
user_agent	http_user_agent

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: 1