Windows Node.exe Executing JS Script In Immediate Folder

Name:Windows Node.exe Executing JS Script In Immediate Folder
id:b22af614-2e48-4d43-aea2-93017500ef0c
version:1
date:None
author:Onur Mustafa Erdogan, Splunk
status:production
type:TTP
Description:The following analytic identifies `node.exe` directly executing a single `.js` script located in the same directory it was launched from, where that directory is an unusual location such as a user profile, PerfLogs, ProgramData, or Temp folder. Legitimate Node.js application, module, and package manager directories are excluded. This pattern is commonly associated with malware loaders and second-stage payloads that leverage the Node.js runtime to execute JavaScript outside of a typical development or application context.
Data_source:

• -Sysmon EventID 1
• -Windows Event Log Security 4688
• -CrowdStrike ProcessRollup2

search:| tstats `security_content_summariesonly`
count min(_time) as firstTime
max(_time) as lastTime

FROM datamodel=Endpoint.Processes WHERE

(
Processes.process_name="node.exe"
OR
Processes.original_file_name="node.exe"
)
Processes.process="*js"
Processes.process_path IN (
"*:\\PerfLogs\\*",
"*:\\ProgramData\\*",
"*:\\Temp\\*",
"*:\\Users\\*"
)
(
NOT Processes.process_path IN (
"*\\AppData\\Roaming\\*",
"*\\node\\*",
"*\\nodejs\\*",
"*\\nvm\\*"
)
AND
(
NOT Processes.process_path = "*\\AppData\\Local\\*"
OR
Processes.process_path = "*\\AppData\\Local\\Temp\\*"
)
)

by Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec
Processes.parent_process_guid Processes.parent_process_id
Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id
Processes.process_integrity_level Processes.process_name
Processes.process_path Processes.user Processes.user_id
Processes.process_current_directory Processes.vendor_product

| `drop_dm_object_name(Processes)`

| eval process_args=split(process, " ")
| eval script_name=mvindex(process_args, 1)
| eval process_args_count=mvcount(process_args)
| regex script_name="(?i)^[^\\\/]+\.js$"
| where like(process_path, process_current_directory.process_name) AND process_args_count=2

| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `windows_node_exe_executing_js_script_in_immediate_folder_filter`

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:Legitimate custom Node.js tooling or utility scripts that are intentionally placed and executed from a user profile, PerfLogs, ProgramData, or Temp directory may trigger this analytic.
References:
  -https://www.bluevoyant.com/blog/clickfix-to-nodejs-rat
  -https://www.microsoft.com/en-us/security/blog/2026/05/20/mini-shai-hulud-compromised-antv-npm-packages-enable-ci-cd-credential-theft/
drilldown_searches:
 name:'View the detection results for - "$dest$"'
 search:'%original_detection_search% | search dest = "$dest$"'
 earliest_offset:'$info_min_time$'
 latest_offset:'$info_max_time$'
 name:'View risk events for the last 7 days for - "$dest$"'
 search:'| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$dest$") | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
 earliest_offset:'7d'
 latest_offset:'0'
analytic_story:['Compromised Windows Host', 'Fake CAPTCHA Campaigns', 'Windows Post-Exploitation']

asset_type:Endpoint

mitre_attack_id:['T1059.007']

product:['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud']

category:endpoint

security_domain:endpoint

tags:

tests:
 name:'True Positive Test'
 attack_data:
  data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1059.007/node_execute_js_script/node_execute_js_script.log
  source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
  sourcetype: XmlWinEventLog
 test_type:'unit'
manual_test:None