Detection: Linux Kernel Module Enumeration
Description
The following analytic identifies the use of the 'kmod' process to list kernel modules on a Linux system. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. While listing kernel modules is not inherently malicious, it can be a precursor to loading unauthorized modules using 'insmod'. If confirmed malicious, this activity could allow an attacker to load kernel modules, potentially leading to privilege escalation, persistence, or other malicious actions within the system.
Search
1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
3 WHERE Processes.process_name=kmod Processes.process IN ("*lsmod*", "*list*")
4 BY Processes.action Processes.dest Processes.original_file_name
5 Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
6 Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
7 Processes.process Processes.process_exec Processes.process_guid
8 Processes.process_hash Processes.process_id Processes.process_integrity_level
9 Processes.process_name Processes.process_path Processes.user
10 Processes.user_id Processes.vendor_product
11
12| `drop_dm_object_name(Processes)`
13
14| `security_content_ctime(firstTime)`
15
16| `security_content_ctime(lastTime)`
17
18| `linux_kernel_module_enumeration_filter`
Data Source
Macros Used
| Name |
Value |
| security_content_ctime |
convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$) |
| linux_kernel_module_enumeration_filter |
search * |
linux_kernel_module_enumeration_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Annotations
| ID |
Technique |
Tactic |
| T1014 |
Rootkit |
Stealth |
| T1082 |
System Information Discovery |
Discovery |
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 the process GUID, process name, and parent process. Additionally, you must ingest complete command-line executions. 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 Processes 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
False positives are present based on automated tooling or system administrative usage. Filter as needed.
Associated Analytic Story
| Message |
Entity Field |
Entity Type |
Risk Score |
| An instance of $parent_process_name$ spawning $process_name$ was identified on endpoint $dest$ by user $user$ enumeration kernel modules. |
user |
user |
20 |
| An instance of $parent_process_name$ spawning $process_name$ was identified on endpoint $dest$ by user $user$ enumeration kernel modules. |
dest |
system |
20 |
Threat Objects
| Field |
Type |
| process_name |
process_name |
| parent_process_name |
parent_process_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: 13