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Description

The following analytic identifies path traversal command-line execution and should be used to tune and driver other more higher fidelity analytics. This technique was seen in malicious document that execute malicious code using msdt.exe and path traversal technique that serve as defense evasion. This Hunting query is a good pivot to look for possible suspicious process and command-line that runs execute path traversal technique to run malicious code. This may help you to find possible downloaded malware or other lolbin execution.

  • Type: Hunting
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2022-06-01
  • Author: Teoderick Contreras, Michael Haag, Splunk
  • ID: d0026380-b3c4-4da0-ac8e-02790063ff6b

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1059 Command and Scripting Interpreter Execution
Kill Chain Phase
  • Installation
NIST
  • DE.AE
CIS20
  • CIS 10
CVE 


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| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes  by Processes.original_file_name Processes.process_id Processes.parent_process_id Processes.process_hash Processes.dest Processes.user Processes.parent_process Processes.process_name Processes.process 
| `drop_dm_object_name("Processes")` 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| eval count_of_pattern1 = (mvcount(split(process,"/.."))-1) 
| eval count_of_pattern2 = (mvcount(split(process,"\.."))-1) 
| eval count_of_pattern3 = (mvcount(split(process,"\\.."))-1) 
| eval count_of_pattern4 = (mvcount(split(process,"//.."))-1) 
| search count_of_pattern1 > 1 OR count_of_pattern2 > 1 OR count_of_pattern3 > 1 OR count_of_pattern4 > 1 
| `windows_command_and_scripting_interpreter_hunting_path_traversal_filter`

Macros

The SPL above uses the following Macros:

:information_source: windows_command_and_scripting_interpreter_hunting_path_traversal_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

  • _time
  • Processes.dest
  • Processes.user
  • Processes.parent_process_name
  • Processes.parent_process
  • Processes.original_file_name
  • Processes.process_name
  • Processes.process
  • Processes.process_id
  • Processes.parent_process_path
  • Processes.process_path
  • Processes.parent_process_id

How To Implement

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 positive may vary depends on the score you want to check. The bigger number of path traversal string count the better.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
36.0 60 60 A parent process $parent_process_name$ has spawned a child $process_name$ with path traversal commandline $process$ in $dest$

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Reference

Test Dataset

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 | version: 1