Try in Splunk Security Cloud

Description

The following analytic identifies parent processes, browsers, Windows terminal applications, Office Products and Java spawning cmd.exe. By its very nature, many applications spawn cmd.exe natively or built into macros. Much of this will need to be tuned to further enhance the risk.

  • Type: Anomaly

  • Product: Splunk Behavioral Analytics

  • Last Updated: 2022-03-01
  • Author: Ignacio Bermudez Corrales, Splunk
  • ID: c10a18cb-fd80-4ffa-a844-25026e0a0c94

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 


1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22



 
| from read_ba_enriched_events() 
| eval timestamp = ucast(map_get(input_event,"time"),"long", null) 
| eval metadata = ucast(map_get(input_event, "metadata"),"map<string, any>", null) 
| eval metadata_uid = ucast(map_get(metadata, "uid"),"string", null) 
| eval process=ucast(map_get(input_event,"process"), "map<string, any>", null) 
| eval process_pid=ucast(map_get(process,"pid"), "string", null) 
| eval process_file=ucast(map_get(process,"file"), "map<string, any>", null) 
| eval process_file_path=ucast(map_get(process_file,"path"), "string", null) 
| eval process_file_name=ucast(map_get(process_file,"name"), "string", null) 
| eval process_cmd_line=ucast(map_get(process,"cmd_line"), "string", null) 
| eval actor=ucast(map_get(input_event,"actor"), "map<string, any>", null) 
| eval actor_user=ucast(map_get(actor,"user"), "map<string, any>", null) 
| eval actor_user_name=ucast(map_get(actor_user,"name"), "string", null) 
| eval actor_process=ucast(map_get(actor,"process"), "map<string, any>", null) 
| eval actor_process_pid=ucast(map_get(actor_process,"pid"), "string", null) 
| eval actor_process_file=ucast(map_get(actor_process,"file"), "map<string, any>", null) 
| eval actor_process_file_path=ucast(map_get(actor_process_file,"path"), "string", null) 
| eval actor_process_file_name=ucast(map_get(actor_process_file,"name"), "string", null) 
| eval device=ucast(map_get(input_event,"device"), "map<string, any>", null) 
| eval device_hostname=ucast(map_get(device,"hostname"), "string", null) 
| where ((actor_process_file_name="winword.exe" OR actor_process_file_name="excel.exe" OR actor_process_file_name="outlook.exe" OR actor_process_file_name="acrobat.exe" OR actor_process_file_name="acrord32.exe" OR actor_process_file_name="iexplore.exe" OR actor_process_file_name="opera.exe" OR actor_process_file_name="firefox.exe" OR actor_process_file_name="powershell.exe") OR (actor_process_file_name="java.exe" AND (NOT match_regex(actor_process_file_name, /(?i)patch1-Hotfix1a/)=true)) OR (actor_process_file_name="chrome.exe" AND (NOT process_cmd_line="chrome-extension"))) AND process_file_name="cmd.exe" --finding_report--

Macros

The SPL above uses the following Macros:

:information_source: detect_prohibited_applications_spawning_cmd_exe_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.

  • process.pid
  • process.file.path
  • process.file.name
  • process.cmd_line
  • actor.user.name
  • actor.process.pid
  • actor.process.file.path
  • actor.process.file.name
  • device.hostname

How To Implement

In order to successfully implement this analytic, you will need endpoint process data from a EDR product or Sysmon. This search has been modified to process raw sysmon data from attack_range's nxlogs on DSP.

Known False Positives

There are circumstances where an application may legitimately execute and interact with the Windows command-line interface.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
35.0 70 50 An instance of $parent_process_name$ spawning $process_name$ was identified on endpoint $dest_device_id$ by user $dest_user_id$, producing a suspicious event that warrants investigating.

: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: 4