Msmpeng Application DLL Side Loading
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: 2023-03-15
- Author: Teoderick Contreras, Splunk, Sanjay Govind
- ID: 8bb3f280-dd9b-11eb-84d5-acde48001122
Annotations
ATT&CK
Kill Chain Phase
- Installation
- Exploitation
NIST
- DE.CM
CIS20
- CIS 10
CVE
Search
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|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 NOT (Filesystem.file_path IN ("*\\Program Files\\windows defender\\*","*\\WinSxS\\*defender-service*","*\\WinSxS\\Temp\\*defender-service*")) by Filesystem.file_create_time Filesystem.process_id Filesystem.file_name Filesystem.user
| `drop_dm_object_name(Filesystem)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `msmpeng_application_dll_side_loading_filter`
Macros
The SPL above uses the following Macros:
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 |
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: 3