Detection: Linux Kernel Module Enumeration

Updated Date: 2024-08-14 ID: 6df99886-0e04-4c11-8b88-325747419278 Author: Michael Haag, Splunk Type: Anomaly Product: Splunk Enterprise Security

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 where Processes.process_name=kmod Processes.process IN ("*lsmod*", "*list*") by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.process Processes.process_id Processes.parent_process_id 
3| `drop_dm_object_name(Processes)` 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)` 
6| `linux_kernel_module_enumeration_filter`

Data Source

Name	Platform	Sourcetype	Source	Supported App
Sysmon for Linux EventID 1	Linux	`'sysmon:linux'`	`'Syslog:Linux-Sysmon/Operational'`	N/A

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

- MITRE ATT&CK

+ Kill Chain Phases

+ NIST

+ CIS

- Threat Actors

ID	Technique	Tactic
T1082	System Information Discovery	Discovery
T1014	Rootkit	Defense Evasion

KillChainPhase.EXPLOITAITON

NistCategory.DE_AE

Cis18Value.CIS_10

APT18

APT19

APT3

APT32

APT37

APT38

APT41

Aquatic Panda

Blue Mockingbird

Chimera

Confucius

Darkhotel

FIN13

FIN8

Gamaredon Group

HEXANE

Higaisa

Inception

Ke3chang

Kimsuky

Lazarus Group

Magic Hound

Malteiro

Moses Staff

MuddyWater

Mustang Panda

Mustard Tempest

OilRig

Patchwork

Rocke

Sandworm Team

SideCopy

Sidewinder

Sowbug

Stealth Falcon

TA2541

TeamTNT

ToddyCat

Tropic Trooper

Turla

Volt Typhoon

Windigo

Windshift

Wizard Spider

ZIRCONIUM

admin@338

APT28

APT41

Rocke

TeamTNT

Winnti Group

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 Risk Event	True

This configuration file applies to all detections of type anomaly. These detections will use Risk Based Alerting.

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

Linux Rootkit

Risk Based Analytics (RBA)

Risk Message	Risk Score	Impact	Confidence
An instance of $parent_process_name$ spawning $process_name$ was identified on endpoint $dest$ by user $user$ enumeration kernel modules.	15	30	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

https://man7.org/linux/man-pages/man8/kmod.8.html

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: 3