[New Hunt] Persistence via Desktop Bus (D-Bus)

[Aegrah]

Summary

This hunt adds several new queries to detect D-Bus persistence techniques.

1

2

3

[github-actions]

Hunt: New - Guidelines

Welcome to the hunting folder within the detection-rules repository! This directory houses a curated collection of threat hunting queries designed to enhance security monitoring and threat detection capabilities using the Elastic Stack.

Documentation and Context

• Detailed description of the Hunt.
• Link related issues or PRs.
• Include references.
• Field Usage: Ensure standardized fields for compatibility across different data environments and sources.

Hunt Metadata Checks

• author: The name of the individual or organization authoring the rule.
• uuid: Unique UUID.
• name and description are descriptive and typo-free.
• language: The query language(s) used in the rule, such as KQL, EQL, ES|QL, OsQuery, or YARA.
• query is inclusive, not overly exclusive, considering performance for diverse environments.
• integration aligns with the index. Ensure updates if the integration is newly introduced.
• notes includes additional information regarding data collected from the hunting query.
• mitre matches appropriate technique and sub-technique IDs that hunting query collect's data for.
• references are valid URL links that include information relevenat to the hunt or threat.
• license

Testing and Validation

• Evidence of testing and valid query usage.
• Markdown Generated: Run python -m hunting generate-markdown with specific parameters to ensure a markdown version of the hunting TOML files is created.
• Index Refreshed: Run python -m hunting refresh-index to refresh indexes.
• Run Unit Tests: Run pytest tests/test_hunt_data.py to run unit tests.