Windows Alternate DataStream - Process Execution
Description
The following analytic detects when a process attempts to execute a file from within an NTFS file system alternate data stream. This detection leverages process execution data from sources like Windows process monitoring or Sysmon Event ID 1, focusing on specific processes known for such behavior. This activity is significant because alternate data streams can be used by threat actors to hide malicious code, making it difficult to detect. If confirmed malicious, this could allow an attacker to execute hidden code, potentially leading to unauthorized actions and further compromise of the system.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2024-05-16
- Author: Steven Dick
- ID: 30c32c5c-41fe-45db-84fe-275e4320da3f
Annotations
ATT&CK
Kill Chain Phase
- Exploitation
NIST
- DE.CM
CIS20
- CIS 10
CVE
Search
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| tstats count min(_time) as firstTime max(_time) as lastTime values(Processes.process_current_directory) as directory from datamodel=Endpoint.Processes where Processes.parent_process_name != "unknown" Processes.process_name IN ("appvlp.exe","bitsadmin.exe","control.exe","cscript.exe","forfiles.exe","ftp.exe","mavinject.exe","mshta.exe","powershell.exe","powershell_ise.exe","pwsh.exe","regini.exe","regscr32.exe","rundll32.exe","sc.exe","wmic.exe","wscript.exe") by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.process Processes.process_id Processes.parent_process_id
| `drop_dm_object_name(Processes)`
| regex process="(\b)\w+(\.\w+)?:\w+(\.\w{2,4})(?!\.)(\b
|\s
|&)"
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `windows_alternate_datastream___process_execution_filter`
Macros
The SPL above uses the following Macros:
windows_alternate_datastream_-_process_execution_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.process_name
- Processes.process
- Processes.process_id
- Processes.parent_process_id
How To Implement
Target environment must ingest process execution data sources such as Windows process monitoring and/or Sysmon EventID 1.
Known False Positives
False positives may be generated by process executions within the commandline, regex has been provided to minimize the possibilty.
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
80.0 | 100 | 80 | The $process_name$ process was executed by $user$ using data from an NTFS alternate data stream. |
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://gist.github.com/api0cradle/cdd2d0d0ec9abb686f0e89306e277b8f
- https://car.mitre.org/analytics/CAR-2020-08-001/
- https://blogs.juniper.net/en-us/threat-research/bitpaymer-ransomware-hides-behind-windows-alternate-data-streams
- https://blog.netwrix.com/2022/12/16/alternate_data_stream/
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