Detection: Linux Auditd Hidden Files And Directories Creation

Updated Date: 2025-01-16 ID: 555cc358-bf16-4e05-9b3a-0f89c73b7261 Author: Teoderick Contreras, Splunk Type: TTP Product: Splunk Enterprise Security

Description

The following analytic detects suspicious creation of hidden files and directories, which may indicate an attacker's attempt to conceal malicious activities or unauthorized data. Hidden files and directories are often used to evade detection by security tools and administrators, providing a stealthy means for storing malware, logs, or sensitive information. By monitoring for unusual or unauthorized creation of hidden files and directories, this analytic helps identify potential attempts to hide or unauthorized creation of hidden files and directories, this analytic helps identify potential attempts to hide malicious operations, enabling security teams to uncover and address hidden threats effectively.

Search

1`linux_auditd` `linux_auditd_normalized_execve_process` 
2| rename host as dest 
3| rename comm as process_name 
4| rename exe as process 
5| where (LIKE (process_exec,"%touch %") OR LIKE (process_exec,"%mkdir %")OR LIKE (process_exec,"%vim %") OR LIKE (process_exec,"%vi %") OR LIKE (process_exec,"%nano %")) AND (LIKE (process_exec,"% ./.%")  OR LIKE (process_exec," .%")OR LIKE (process_exec," /.%")) 
6| stats count min(_time) as firstTime max(_time) as lastTime by argc process_exec dest 
7| `security_content_ctime(firstTime)` 
8| `security_content_ctime(lastTime)`
9| `linux_auditd_hidden_files_and_directories_creation_filter`

Data Source

Name	Platform	Sourcetype	Source
Linux Auditd Execve	Linux	`'linux:audit'`	`'/var/log/audit/audit.log'`

Macros Used

Name	Value
linux_auditd	`sourcetype="linux:audit"`
linux_auditd_hidden_files_and_directories_creation_filter	`search *`

linux_auditd_hidden_files_and_directories_creation_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
T1083	File and Directory Discovery	Discovery

Exploitation

DE.CM

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 Notable	Yes
Rule Title	`%name%`
Rule Description	`%description%`
Notable Event Fields	user, dest
Creates Risk Event	True

This configuration file applies to all detections of type TTP. These detections will use Risk Based Alerting and generate Notable Events.

Implementation

To implement this detection, the process begins by ingesting auditd data, that consists of SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line executions and process details on Unix/Linux systems. These logs should be ingested and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833), which is essential for correctly parsing and categorizing the data. The next step involves normalizing the field names to match the field names set by the Splunk Common Information Model (CIM) to ensure consistency across different data sources and enhance the efficiency of data modeling. This approach enables effective monitoring and detection of linux endpoints where auditd is deployed

Known False Positives

Administrator or network operator can use this application for automation purposes. Please update the filter macros to remove false positives.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message:

A [$process_exec$] event occurred on host - [$dest$].

Risk Object	Risk Object Type	Risk Score	Threat Objects
dest	system	64	No Threat Objects

References

Detection Testing

Test Type	Status	Dataset	Source	Sourcetype
Validation	✅ Passing	N/A	N/A	N/A
Unit	✅ Passing	Dataset	`/var/log/audit/audit.log`	`linux:audit`
Integration	✅ Passing	Dataset	`/var/log/audit/audit.log`	`linux:audit`

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: 4