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Neural Foundry's avatar

Nice breakdown of the agent workflow here. The part about using LLMs to bridge the gap between endpoint discovery and actualy exploitation is key - tools like LinkFinder have always left us with a bunch of URLs that still need manual triage to figure out what headers or auth are needed. I've spent way too many hours on that exact problem in bounty programs, so seeing it tackled with something like analyze_js_for_requirements makes a lot of sense. One thing I'm curious about though is how well this handles obfuscated JS or when the actual secrets are fetched dynamically rather than hardcoded. Does the agent degrade gracefuly in those cases or does it just give up?

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Anshuman Bhartiya's avatar

I built this POC almost a year ago and haven't really spent a lot of time in making the agent better since then. This was mostly an attempt to show that anybody could build similar offensive agents.

To answer your question though, I believe there could be a multi agent architecture such that if obfuscated jS is found, there could be a specialized subagent that can help with de-obfuscation of that jS and/or help retrieve secrets dynamically based on the URLs. This is all doable now. With subagents, hooks and skills - building a multi agentic architecture that handles such edge cases is definitely possible.

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