ID | Technique | Tactic |
---|---|---|
T1036 | Masquerading | Defense Evasion |
T1036.003 | Rename System Utilities | Defense Evasion |
T1218.011 | Rundll32 | Defense Evasion |
Detection: Windows LOLBAS Executed As Renamed File
Description
The following analytic identifies a LOLBAS process being executed where it's process name does not match it's original file name attribute. Processes that have been renamed and executed may be an indicator that an adversary is attempting to evade defenses or execute malicious code. The LOLBAS project documents Windows native binaries that can be abused by threat actors to perform tasks like executing malicious code.
Search
1
2| tstats `security_content_summariesonly` latest(Processes.parent_process) as parent_process, latest(Processes.process) as process, latest(Processes.process_guid) as process_guid count, min(_time) AS firstTime, max(_time) AS lastTime FROM datamodel=Endpoint.Processes where NOT Processes.original_file_name IN("-","unknown") AND NOT Processes.process_path IN ("*\\Program Files*","*\\PROGRA~*","*\\Windows\\System32\\*","*\\Windows\\Syswow64\\*") BY Processes.user Processes.dest Processes.parent_process_name Processes.process_name Processes.original_file_name Processes.process_path
3|`drop_dm_object_name(Processes)`
4| where NOT match(process_name, "(?i)".original_file_name)
5| lookup lolbas_file_path lolbas_file_name as original_file_name OUTPUT description as desc
6| search desc!="false"
7| `security_content_ctime(firstTime)`
8| `security_content_ctime(lastTime)`
9| `windows_lolbas_executed_as_renamed_file_filter`
Data Source
Name | Platform | Sourcetype | Source | Supported App |
---|---|---|---|---|
CrowdStrike ProcessRollup2 | N/A | 'crowdstrike:events:sensor' |
'crowdstrike' |
N/A |
Macros Used
Name | Value |
---|---|
security_content_ctime | convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$) |
windows_lolbas_executed_as_renamed_file_filter | search * |
windows_lolbas_executed_as_renamed_file_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
A certain amount of false positives are likely with this detection. MSI based installers often trigger for SETUPAPL.dll and vendors will often copy system exectables to a different path for application usage.
Associated Analytic Story
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
The file originally named $original_file_name$ was executed as $process_name$ on $dest$ | 40 | 80 | 50 |
References
Detection Testing
Test Type | Status | Dataset | Source | Sourcetype |
---|---|---|---|---|
Validation | ✅ Passing | N/A | N/A | N/A |
Unit | ✅ Passing | Dataset | XmlWinEventLog:Microsoft-Windows-Sysmon/Operational |
xmlwineventlog |
Integration | ✅ Passing | Dataset | XmlWinEventLog:Microsoft-Windows-Sysmon/Operational |
xmlwineventlog |
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: 1