ID | Technique | Tactic |
---|---|---|
T1070 | Indicator Removal | Defense Evasion |
Detection: Linux Indicator Removal Clear Cache
Description
The following analytic detects processes that clear or free page cache on a Linux system. It leverages Endpoint Detection and Response (EDR) data, focusing on specific command-line executions involving the kernel system request drop_caches
. This activity is significant as it may indicate an attempt to delete forensic evidence or the presence of wiper malware like Awfulshred. If confirmed malicious, this behavior could allow an attacker to cover their tracks, making it difficult to investigate other malicious activities or system compromises.
Search
1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name IN ("dash", "sudo", "bash") AND Processes.process IN("* echo 3 > *", "* echo 2 > *","* echo 1 > *") AND Processes.process = "*/proc/sys/vm/drop_caches" by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.process Processes.process_id Processes.parent_process_id Processes.process_guid
3| `drop_dm_object_name(Processes)`
4| `security_content_ctime(firstTime)`
5| `linux_indicator_removal_clear_cache_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_indicator_removal_clear_cache_filter | search * |
linux_indicator_removal_clear_cache_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 Notable | Yes |
Rule Title | %name% |
Rule Description | %description% |
Notable Event Fields | user, dest |
Creates Risk Event | True |
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
unknown
Associated Analytic Story
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
a $process_name$ clear cache using kernel drop cache system request in $dest$ | 49 | 70 | 70 |
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: 2