GSOC'24 Enhancing Capa Usability with an Improved CLI and a Potential Web UI

[Atlas-64]

Hi team (@williballenthin, @mike-hunhoff, @mr-tz),
I'm starting this discussion to express my interest in applying for GSOC'24 under FLARE. I am interested in improving the CLI's understandability, making it more intuitive to navigate, and helping new users acclimatize to Capa faster.

Even though the information is categorized, Capa's current output can be overwhelming for new users. To improve user experience, we can explore ways to make navigating and understanding the results more accessible. This will allow users to quickly identify relevant details and take appropriate actions against potential malware. ( I would love to take feedback directly from the community while attempting to do this, and this will also help us tackle building the WEB-based GUI)
personally, to give an example of a case where I was running Capa while trying to understand its limitations and ran it on the wannacry malware, I was amazed at its ability to break down its attack structure. However, I noticed that if I hadn't been learning a lab specifically for malware analysis, it would have been much more challenging to understand the output it was showing. I would love to hear the community's opinion on where we could close this gap for them to use it in a less daunting way.

For instance, in the screenshot below, the "MBC Objectives" section displays a long list of technical terms, making it difficult for beginners to grasp the overall risk the program poses. (I am excited to see how having a web-based GUI could help visualize the output a lot better )

A section I would like to know about from the mentors is getting feedback from the community since this would be an overhaul of the central CLI. Feedback has a considerable role to play. Should I include a detailed section within my proposal about how I would tackle it? (lemme know if I have the wrong train of thought :D )
Also, I understand as a beginner, my lack of familiarity with the code base would require some help from your side, especially during the initial quarter of the program, to identify performance bottlenecks and improve its ability to detect capabilities on large datasets, simplifying the installation by reducing its dependencies and overall increasing its execution.

Feel free to share your thoughts on this approach, point out any potential issues, and suggest additional issues I could tackle. I'm eager to hear your feedback!

To get your feedback, can I share the draft proposal via Google Docs or another platform?

Thank you,
@Atlas-64

[mr-tz]

Hey @Atlas-64, your ideas sound good and you seem to have a good plan. Of course, we're around to provide any support we can.
Unfortunately, we can't provide feedback on the proposals during the last 9 days of the application window.