Reg exe used to hide files directories via registry keys
THIS IS A DEPRECATED DETECTION
This detection has been marked deprecated by the Splunk Threat Research team. This means that it will no longer be maintained or supported.
Description
The search looks for command-line arguments used to hide a file or directory using the reg add command.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2019-02-27
- Author: Bhavin Patel, Splunk
- ID: 61a7d1e6-f5d4-41d9-a9be-39a1ffe69459
Annotations
Kill Chain Phase
- Actions on Objectives
NIST
- DE.CM
CIS20
- CIS 8
CVE
Search
1
2
3
4
5
6
7
| tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = reg.exe Processes.process="*add*" Processes.process="*Hidden*" Processes.process="*REG_DWORD*" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
|`security_content_ctime(lastTime)`
| regex process = "(/d\s+2)"
| `reg_exe_used_to_hide_files_directories_via_registry_keys_filter`
Macros
The SPL above uses the following Macros:
reg_exe_used_to_hide_files_directories_via_registry_keys_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
How To Implement
You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model.
Known False Positives
None at the moment
Associated Analytic Story
- Windows Defense Evasion Tactics
- Suspicious Windows Registry Activities
- Windows Persistence Techniques
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
25.0 | 50 | 50 | tbd |
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: 2