Comment by dzaima
17 hours ago
The most difficult parts of getting readable code would be dealing with inlined functions and otherwise-duplicated code from macros or similar, and dealing with in-memory structure layouts; both pretty complicated very-global tasks. (never mind naming things, but perhaps LLMs have a good shot at that)
That said, chatgpt currently seems to fail even basic things - completely missed the `thrM` path being possible here: https://chatgpt.com/share/69296a8e-d620-800b-8c25-15f4260c78... https://dzaima.github.io/paste/#0jZJNTsMwEIX3OcWoSFWCqrhN0wb... and that's only basic bog-standard branching, no in-memory structures or stack usage (such trivial problems could be handled by using an actual proper disassembler before throwing an LLM at that wall, but of course that only solves the easy part)
You can't feed something like that to the free ChatGPT model and expect anything useful. Try these:
https://chatgpt.com/s/t_6929f00ff5508191b75f31e219609a35 (5.1 Pro Thinking)
https://claude.ai/share/7d9caa25-14f7-4233-b15c-d32b86e20e09 (Opus 4.5)
https://docs.google.com/document/d/1C0lSKbLSZOyMWnGgR0QhZh3Q... (Gemini 3 Pro Thinking)
All of them recognized the thrM exception path, although I didn't review them for correctness.
That being said, I imagine the major showstopper in real-world disassembly tasks would simply be the limited context size. As you suggest, a standard LLM isn't really the best tool for the job, at least not without assistance to split up the task logically.
Those first two indeed look correct (third link is not public); indeed free chatgpt is understandably not the best, but I did give it basically the smallest function in my codebase that does something meaningful, instead of any of the actually-non-trivial multi-kilobyte functions doing realistic things needing context.
Would be interesting to push the models with a couple of larger functions, if you have some links you'd like me to try.
I have paid pro accounts on all three, but for some reason Gemini is no longer allowing links to be shared on some queries including this one. All it would let me do is export it to Docs, which I thought would be publicly visible but evidently isn't.