Question 1

How to integrate FSF with Splunk for alerting on scan results?

Accepted Answer

FSF outputs JSON logs that can be aggregated and indexed in Splunk or ELK stacks for alerting. The README suggests this approach, allowing you to build custom dashboards and notifications based on scan data, such as Yara hits or module outputs.

Question 2

What's the difference between FSF and using Yara alone for malware analysis?

Accepted Answer

FSF extends Yara by enabling recursive extraction and modular actions based on signature hits. While Yara only detects patterns, FSF uses those detections to trigger automated extraction of embedded objects and metadata enrichment, turning static analysis into actionable intelligence.

Question 3

How to write a custom module for FSF to handle a new file type?

Accepted Answer

Custom modules are written in Python by defining logic that executes when specific Yara rules fire. The docs/modules.md provides a primer on module development, including structure examples and how to integrate new modules for tasks like parsing unique malware configs or file formats.

Question 4

Can FSF analyze encrypted or password-protected archives?

Accepted Answer

FSF's built-in modules, such as EXTRACT_ZIP and EXTRACT_RAR, focus on standard extraction and may not handle encrypted or password-protected files without additional logic. Analysts would need to develop custom modules or pre-process files to manage encryption, limiting out-of-the-box functionality.

Question 5

Is FSF good for real-time network monitoring with tools like Bro?

Accepted Answer

FSF can integrate with Bro for automated file extraction from network traffic, as described in the 'Automated File Extraction' section. However, it's optimized for batch processing and post-incident analysis rather than real-time detection, due to potential latency from recursive scanning and server processing.

Question 6

How to use jq to filter FSF JSON output for specific threats?

Accepted Answer

FSF's JSON output can be filtered with jq to isolate data like suspicious macro extractions or PE metadata. The docs/jq_examples.md includes practical filters, such as selecting objects where alert flags are set or extracting author fields from documents, enabling targeted threat hunting.

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