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Description

This search is to detect suspicious loading of dll in specific path relative to printnightmare exploitation. In this search we try to detect the loaded modules made by spoolsv.exe after the exploitation.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2021-07-01
  • Author: Mauricio Velazco, Michael Haag, Teoderick Contreras, Splunk
  • ID: a5e451f8-da81-11eb-b245-acde48001122

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1547.012 Print Processors Persistence, Privilege Escalation
T1547 Boot or Logon Autostart Execution Persistence, Privilege Escalation
Kill Chain Phase
  • Exploitation
NIST
CIS20
CVE
1
2
3
4
5
6
`sysmon` EventCode=7 Image ="*\\spoolsv.exe" ImageLoaded="*\\Windows\\System32\\spool\\drivers\\x64\\*" ImageLoaded = "*.dll" 
| stats dc(ImageLoaded) as countImgloaded values(ImageLoaded) as ImgLoaded count min(_time) as firstTime max(_time) as lastTime by Image Computer ProcessId EventCode 
| where countImgloaded >= 3 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `spoolsv_suspicious_loaded_modules_filter`

Macros

The SPL above uses the following Macros:

:information_source: spoolsv_suspicious_loaded_modules_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
  • Image
  • Computer
  • EventCode
  • ImageLoaded

How To Implement

To successfully implement this search, you need to be ingesting logs with the process name and imageloaded executions from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA.

Known False Positives

unknown

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
72.0 80 90 $Image$ with process id $process_id$ has loaded a driver from $ImageLoaded$ on endpoint $Computer$. This behavior is suspicious and related to PrintNightmare.

: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: 2