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Description

This search is to detect a suspicious creation of msmpeng.exe or mpsvc.dll in non default windows defender folder. This technique was seen couple days ago with revil ransomware in Kaseya Supply chain. The approach is to drop an old version of msmpeng.exe to load the actual payload name as mspvc.dll which will load the revil ransomware to the compromise machine

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2021-07-05
  • Author: Teoderick Contreras, Splunk
  • ID: 8bb3f280-dd9b-11eb-84d5-acde48001122

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1574.002 DLL Side-Loading Persistence, Privilege Escalation, Defense Evasion
T1574 Hijack Execution Flow Persistence, Privilege Escalation, Defense Evasion
Kill Chain Phase
  • Exploitation
NIST
CIS20
CVE
1
2
3
4
5
6
|tstats `security_content_summariesonly` values(Filesystem.file_path) as file_path count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Filesystem where (Filesystem.file_name = "msmpeng.exe" OR Filesystem.file_name = "mpsvc.dll")  AND Filesystem.file_path != "*\\Program Files\\windows defender\\*" by Filesystem.file_create_time Filesystem.process_id  Filesystem.file_name Filesystem.user 
| `drop_dm_object_name(Processes)` 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `msmpeng_application_dll_side_loading_filter`

Macros

The SPL above uses the following Macros:

:information_source: msmpeng_application_dll_side_loading_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
  • Filesystem.file_create_time
  • Filesystem.process_id
  • Filesystem.file_name
  • Filesystem.user
  • Filesystem.file_path

How To Implement

To successfully implement this search you need to be ingesting information on process that include the name of the Filesystem responsible for the changes from your endpoints into the Endpoint datamodel in the Filesystem node.

Known False Positives

quite minimal false positive expected.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
25.0 50 50  

: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

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