ID | Technique | Tactic |
---|---|---|
T1059.003 | Windows Command Shell | Execution |
T1059 | Command and Scripting Interpreter | Execution |
Detection: Windows Command Shell DCRat ForkBomb Payload
Description
The following analytic detects the execution of a DCRat "forkbomb" payload, which spawns multiple cmd.exe processes that launch notepad.exe instances in quick succession. This detection leverages Endpoint Detection and Response (EDR) data, focusing on the rapid creation of cmd.exe and notepad.exe processes within a 30-second window. This activity is significant as it indicates a potential DCRat infection, a known Remote Access Trojan (RAT) with destructive capabilities. If confirmed malicious, this behavior could lead to system instability, resource exhaustion, and potential disruption of services.
Search
1
2| 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
3| where parent_process_id_count>= 10 AND process_id_count >=10
4| `drop_dm_object_name(Processes)`
5| `security_content_ctime(firstTime)`
6| `security_content_ctime(lastTime)`
7| `windows_command_shell_dcrat_forkbomb_payload_filter`
Data Source
Name | Platform | Sourcetype | Source | Supported App |
---|---|---|---|---|
CrowdStrike ProcessRollup2 | N/A | 'crowdstrike:events:sensor' |
'crowdstrike' |
N/A |
Macros Used
Name | Value |
---|---|
security_content_ctime | convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$) |
windows_command_shell_dcrat_forkbomb_payload_filter | search * |
windows_command_shell_dcrat_forkbomb_payload_filter
is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Annotations
Default Configuration
This detection is configured by default in Splunk Enterprise Security to run with the following settings:
Setting | Value |
---|---|
Disabled | true |
Cron Schedule | 0 * * * * |
Earliest Time | -70m@m |
Latest Time | -10m@m |
Schedule Window | auto |
Creates Notable | Yes |
Rule Title | %name% |
Rule Description | %description% |
Notable Event Fields | user, dest |
Creates Risk Event | True |
Implementation
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
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
Multiple cmd.exe processes with child process of notepad.exe executed on $dest$ | 81 | 90 | 90 |
References
Detection Testing
Test Type | Status | Dataset | Source | Sourcetype |
---|---|---|---|---|
Validation | ✅ Passing | N/A | N/A | N/A |
Unit | ✅ Passing | Dataset | XmlWinEventLog:Microsoft-Windows-Sysmon/Operational |
xmlwineventlog |
Integration | ✅ Passing | Dataset | XmlWinEventLog:Microsoft-Windows-Sysmon/Operational |
xmlwineventlog |
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: GitHub | Version: 2