Detection: Linux UDEV Rule Created

Description

The following analytic detects the creation of files within udev rules directories, including /etc/udev/rules.d and /usr/lib/udev/rules.d. Adversaries abuse udev rules to achieve persistent code execution by embedding RUN+= directives that trigger arbitrary commands whenever a matching device event occurs, such as a USB device being connected or a network interface coming online. Because udev rules execute in the context of the udev daemon with elevated privileges, this technique can provide both persistence and privilege escalation. It is used by post-exploitation frameworks such as PANIX and is effective on headless servers where device events still fire despite no interactive user session.

 1
 2| tstats `security_content_summariesonly`
 3  count min(_time) as firstTime
 4        max(_time) as lastTime
 5
 6FROM datamodel=Endpoint.Filesystem WHERE
 7
 8Filesystem.file_path IN (
 9    "/etc/udev/rules.d/*",
10    "/usr/lib/udev/rules.d/*"
11)
12
13BY Filesystem.action Filesystem.dest Filesystem.file_access_time
14   Filesystem.file_create_time Filesystem.file_hash Filesystem.file_modify_time
15   Filesystem.file_name Filesystem.file_path Filesystem.process_guid
16   Filesystem.process_id Filesystem.user Filesystem.vendor_product
17
18
19| `drop_dm_object_name(Filesystem)`
20
21| `security_content_ctime(firstTime)`
22
23| `security_content_ctime(lastTime)`
24
25| `linux_udev_rule_created_filter`

Data Source

Name Platform Sourcetype Source
Sysmon for Linux EventID 11 Linux icon Linux 'sysmon:linux' 'Syslog:Linux-Sysmon/Operational'

Macros Used

Name Value
security_content_summariesonly summariesonly=summariesonly_config allow_old_summaries=oldsummaries_config fillnull_value=fillnull_config``
linux_udev_rule_created_filter search *
linux_udev_rule_created_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
T1037 Boot or Logon Initialization Scripts Persistence
T1547 Boot or Logon Autostart Execution Privilege Escalation
Exploitation
Installation
DE.AE
CIS 10

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

The detection is based on data that originates from Endpoint Detection and Response (EDR) agents. These agents are designed to provide security-related telemetry from the endpoints where the agent is installed. To implement this search, you must ingest logs that contain file creation events including the file path and user context. These logs must be processed using the appropriate Splunk Technology Add-ons that are specific to the EDR product. The logs must also be mapped to the Filesystem node of the Endpoint data model. Use the Splunk Common Information Model (CIM) to normalize the field names and speed up the data modeling process.

Known False Positives

Legitimate system administrators or software installers may create udev rules as part of normal hardware configuration or device management tasks. Filter based on known administrative activity and trusted software installations.

Associated Analytic Story

Intermediate Findings

Message Entity Field Entity Type Risk Score
New UDEV rule created under [$file_path$] by [$user$] on [$dest$] dest system 20

Threat Objects

Field Type
file_name file_name

References

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation Passing N/A N/A N/A
Unit Passing Dataset Syslog:Linux-Sysmon/Operational sysmon:linux
Integration ✅ Passing Dataset Syslog:Linux-Sysmon/Operational sysmon:linux

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