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The following analytic identifies path traversal command-line executions, leveraging data from Endpoint Detection and Response (EDR) agents. It detects patterns in command-line arguments indicative of path traversal techniques, such as multiple instances of "/..", "..", or "\..". This activity is significant as it often indicates attempts to evade defenses by executing malicious code, such as through msdt.exe. If confirmed malicious, this behavior could allow attackers to execute arbitrary code, potentially leading to system compromise, data exfiltration, or further lateral movement within the network.

  • Type: Hunting
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2024-05-15
  • Author: Teoderick Contreras, Michael Haag, Splunk
  • ID: d0026380-b3c4-4da0-ac8e-02790063ff6b




ID Technique Tactic
T1059 Command and Scripting Interpreter Execution
Kill Chain Phase
  • Installation
  • DE.AE
  • CIS 10
| 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_name 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`


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


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.


Test Dataset

Replay any dataset to Splunk Enterprise by using our tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range

source | version: 2