ID | Technique | Tactic |
---|---|---|
T1083 | File and Directory Discovery | Discovery |
Detection: Linux Auditd Database File And Directory Discovery
Description
The following analytic detects suspicious database file and directory discovery activities, which may signal an attacker attempt to locate and assess critical database assets on a compromised system. This behavior is often a precursor to data theft, unauthorized access, or privilege escalation, as attackers seek to identify valuable information stored in databases. By monitoring for unusual or unauthorized attempts to locate database files and directories, this analytic aids in early detection of potential reconnaissance or data breach efforts, enabling security teams to respond swiftly and mitigate the risk of further compromise.
Search
1`linux_auditd` `linux_auditd_normalized_execve_process`
2| rename host as dest
3| where (LIKE (process_exec, "%find%") OR LIKE (process_exec, "%grep%")) AND (LIKE (process_exec, "%.db%") OR LIKE (process_exec, "%.sql%") OR LIKE (process_exec, "%.sqlite%") OR LIKE (process_exec, "%.mdb%")OR LIKE (process_exec, "%.accdb%")OR LIKE (process_exec, "%.mdf%")OR LIKE (process_exec, "%.ndf%")OR LIKE (process_exec, "%.ldf%")OR LIKE (process_exec, "%.frm%")OR LIKE (process_exec, "%.idb%")OR LIKE (process_exec, "%.myd%")OR LIKE (process_exec, "%.myi%")OR LIKE (process_exec, "%.dbf%")OR LIKE (process_exec, "%.db2%")OR LIKE (process_exec, "%.dbc%")OR LIKE (process_exec, "%.fpt%")OR LIKE (process_exec, "%.ora%"))
4| stats count min(_time) as firstTime max(_time) as lastTime by argc process_exec dest
5| `security_content_ctime(firstTime)`
6| `security_content_ctime(lastTime)`
7| `linux_auditd_database_file_and_directory_discovery_filter`
Data Source
Name | Platform | Sourcetype | Source | Supported App |
---|---|---|---|---|
Linux Auditd Execve | Linux | 'linux:audit' |
'/var/log/audit/audit.log' |
N/A |
Macros Used
Name | Value |
---|---|
linux_auditd | sourcetype="linux:audit" |
linux_auditd_database_file_and_directory_discovery_filter | search * |
linux_auditd_database_file_and_directory_discovery_filter
is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Annotations
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 |
Implementation
To implement this detection, the process begins by ingesting auditd data, that consist 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 | Risk Score | Impact | Confidence |
---|---|---|---|
A [$process_exec$] event occurred on host - [$dest$] to discover database files and directories. | 25 | 50 | 50 |
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: 2