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The following analytic detects an Office product spawning a CMD process, which is indicative of a macro executing shell commands to download or run malicious code. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process and parent process names. This activity is significant as it often signals the execution of malicious payloads, such as those seen in Trickbot spear-phishing campaigns. If confirmed malicious, this behavior could lead to unauthorized code execution, potentially compromising the system and allowing further malicious activities.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2024-05-24
  • Author: Teoderick Contreras, Splunk
  • ID: b8b19420-e892-11eb-9244-acde48001122




ID Technique Tactic
T1566 Phishing Initial Access
T1566.001 Spearphishing Attachment Initial Access
Kill Chain Phase
  • Delivery
  • DE.CM
  • CIS 10
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.parent_process_name = "winword.exe" OR Processes.parent_process_name= "excel.exe" OR Processes.parent_process_name = "powerpnt.exe" OR Processes.parent_process_name= "onenote.exe" OR Processes.parent_process_name = "onenotem.exe" OR Processes.parent_process_name = "onenoteviewer.exe" OR Processes.parent_process_name = "onenoteim.exe" OR Processes.parent_process_name = "msaccess.exe" OR  Processes.parent_process_name="Graph.exe" OR Processes.parent_process_name="winproj.exe") `process_cmd` by  Processes.parent_process_name Processes.parent_process Processes.process_name Processes.process Processes.process_id Processes.process_guid Processes.user Processes.dest Processes.original_file_name 
| `drop_dm_object_name("Processes")` 
| `security_content_ctime(firstTime)` 
| `office_product_spawn_cmd_process_filter`


The SPL above uses the following Macros:

:information_source: office_product_spawn_cmd_process_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

IT or network admin may create an document automation that will run shell script.

Associated Analytic Story


Risk Score Impact Confidence Message
56.0 70 80 an office product parent process $parent_process_name$ spawn child process $process_name$ in host $dest$

: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

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