Wscript Or Cscript Suspicious Child Process
Description
The following analytic identifies suspicious child processes spawned by WScript or CScript. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific parent and child process names. This activity is significant as adversaries often use WScript or CScript to execute Living Off The Land Binaries (LOLBINs) or other scripts like PowerShell for defense evasion. If confirmed malicious, this behavior could allow attackers to execute arbitrary code, escalate privileges, or maintain persistence within the environment, posing a significant security risk.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2024-05-18
- Author: Teoderick Contreras, Splunk
- ID: 1f35e1da-267b-11ec-90a9-acde48001122
Annotations
ATT&CK
Kill Chain Phase
- Exploitation
- Installation
NIST
- DE.CM
CIS20
- CIS 10
CVE
Search
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| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name IN ("cscript.exe", "wscript.exe") Processes.process_name IN ("regsvr32.exe", "rundll32.exe","winhlp32.exe","certutil.exe","msbuild.exe","cmd.exe","powershell*","wmic.exe","mshta.exe") by Processes.dest Processes.user Processes.parent_process_name Processes.parent_process Processes.process_name Processes.process Processes.process_id Processes.parent_process_id
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `wscript_or_cscript_suspicious_child_process_filter`
Macros
The SPL above uses the following Macros:
wscript_or_cscript_suspicious_child_process_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
Administrators may create vbs or js script that use several tool as part of its execution. Filter as needed.
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
49.0 | 70 | 70 | wscript or cscript parent process spawned $process_name$ in $dest$ |
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://www.hybrid-analysis.com/sample/8da5b75b6380a41eee3a399c43dfe0d99eeefaa1fd21027a07b1ecaa4cd96fdd?environmentId=120
- https://www.microsoft.com/security/blog/2022/01/15/destructive-malware-targeting-ukrainian-organizations/
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