Windows Command Shell DCRat ForkBomb Payload
Description
The following analytic identifies DCRat "forkbomb" payload feature. This technique was seen in dark crystal RAT backdoor capabilities where it will execute several cmd child process executing "notepad.exe & pause". This analytic detects the multiple cmd.exe and child process notepad.exe execution using batch script in the targeted host within 30s timeframe. this TTP can be a good pivot to check DCRat infection.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2022-07-28
- Author: Teoderick Contreras, Splunk
- ID: 2bb1a362-7aa8-444a-92ed-1987e8da83e1
Annotations
ATT&CK
Kill Chain Phase
- Installation
NIST
- DE.CM
CIS20
- CIS 10
CVE
Search
1
2
3
4
5
6
7
| tstats `security_content_summariesonly` values(Processes.process) as process values(Processes.parent_process) as parent_process values(Processes.parent_process_id) as parent_process_id values(Processes.process_id) as process_id dc(Processes.parent_process_id) as parent_process_id_count dc(Processes.process_id) as process_id_count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name= "cmd.exe" (Processes.process_name = "notepad.exe" OR Processes.original_file_name= "notepad.exe") Processes.parent_process = "*.bat*" by Processes.parent_process_name Processes.process_name Processes.original_file_name Processes.parent_process Processes.dest Processes.user _time span=30s
| where parent_process_id_count>= 10 AND process_id_count >=10
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `windows_command_shell_dcrat_forkbomb_payload_filter`
Macros
The SPL above uses the following Macros:
windows_command_shell_dcrat_forkbomb_payload_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
- Processes.dest
- Processes.user
- Processes.parent_process_name
- Processes.parent_process
- Processes.original_file_name
- Processes.process_name
- Processes.process
- Processes.process_id
- Processes.parent_process_path
- Processes.process_path
- Processes.parent_process_id
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
unknown
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
81.0 | 90 | 90 | Multiple cmd.exe processes with child process of notepad.exe executed on $dest$ |
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
- https://cert.gov.ua/article/405538
- https://malpedia.caad.fkie.fraunhofer.de/details/win.dcrat
- https://www.mandiant.com/resources/analyzing-dark-crystal-rat-backdoor
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: 1