Detection: Linux Suspicious XDG Autostart

Description

The following analytic detects the creation of a .desktop file within XDG autostart directories, including the system-wide /etc/xdg/autostart and user-local ~/.config/autostart paths. Adversaries abuse XDG autostart entries to achieve persistence on Linux desktop environments — any .desktop file placed in these directories is automatically executed when a user logs into a graphical session. This technique is used by post-exploitation frameworks such as PANIX to survive reboots without requiring root on user-local paths, or to achieve system-wide persistence when writing to /etc/xdg/autostart.

 1
 2| tstats `security_content_summariesonly`
 3  count min(_time) as firstTime max(_time) as lastTime
 4
 5FROM datamodel=Endpoint.Filesystem WHERE
 6
 7Filesystem.action="created"
 8Filesystem.file_path IN (
 9    "/etc/xdg/autostart/*",
10    "*/.config/autostart/*"
11)
12Filesystem.file_path = "*.desktop"
13
14BY Filesystem.action Filesystem.dest Filesystem.file_access_time
15   Filesystem.file_create_time Filesystem.file_hash Filesystem.file_modify_time
16   Filesystem.file_name Filesystem.file_path Filesystem.process_guid
17   Filesystem.process_id Filesystem.user Filesystem.vendor_product
18
19
20| `drop_dm_object_name(Filesystem)`
21
22| `security_content_ctime(firstTime)`
23
24| `security_content_ctime(lastTime)`
25
26| `linux_suspicious_xdg_autostart_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_suspicious_xdg_autostart_filter search *
linux_suspicious_xdg_autostart_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
T1059.004 Unix Shell Privilege Escalation
T1547 Boot or Logon Autostart Execution Execution
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 software installations may create .desktop files in /etc/xdg/autostart as part of their normal setup process. Filter known software deployment tools and approved administrative activity as needed.

Associated Analytic Story

Intermediate Findings

Message Entity Field Entity Type Risk Score
Possible Suspicious XDG Autostart file 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