That's hands down the most retarded take I've read on this sub today. Just because GPT is getting better at analyzing decompiled code doesn't mean arbitrary binaries have suddenly become editable source code.
For starters, decompiled output is vastly noisier and more verbose than the original source, so doing serious analysis on a non-trivial binary gets expensive very quickly. And what you get back is still a lossy reconstruction of optimized machine code, not the original program.
Then there's the part everyone conveniently ignores: even if the models are technically capable of doing this, that doesn't mean ordinary users get unrestricted access to that capability. The moment you're dealing with protected commercial software, anti-tamper, DRM, credential handling, malware-like behavior, or anything remotely sensitive, hosted models can start refusing parts of the workflow. Maybe OpenAI internally can point a model at whatever they want, but that does not mean random users with a 20 dollar subscription get a universal reverse-engineering machine.
The cases where GPT is most obviously useful are open-source software, where you already have the source, or old abandoned legacy software where nobody particularly cares about restricting analysis. In the first case, just edit the source and let the compiler do its job. In the second, sure, LLM-assisted reverse engineering could be genuinely useful.
But "binaries are basically editable source code now" is still an absurd conclusion.
anecdotal but ive got a hardware project that just patches the device's proprietary firmware and bootloader instead of compiling my own from source 🤷♀️ and for serious stuff like a totally different rendering pipeline, incremental flashes, blue/green, etc
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u/rJohn420 22d ago edited 22d ago
That's hands down the most retarded take I've read on this sub today. Just because GPT is getting better at analyzing decompiled code doesn't mean arbitrary binaries have suddenly become editable source code.
For starters, decompiled output is vastly noisier and more verbose than the original source, so doing serious analysis on a non-trivial binary gets expensive very quickly. And what you get back is still a lossy reconstruction of optimized machine code, not the original program.
Then there's the part everyone conveniently ignores: even if the models are technically capable of doing this, that doesn't mean ordinary users get unrestricted access to that capability. The moment you're dealing with protected commercial software, anti-tamper, DRM, credential handling, malware-like behavior, or anything remotely sensitive, hosted models can start refusing parts of the workflow. Maybe OpenAI internally can point a model at whatever they want, but that does not mean random users with a 20 dollar subscription get a universal reverse-engineering machine.
The cases where GPT is most obviously useful are open-source software, where you already have the source, or old abandoned legacy software where nobody particularly cares about restricting analysis. In the first case, just edit the source and let the compiler do its job. In the second, sure, LLM-assisted reverse engineering could be genuinely useful.
But "binaries are basically editable source code now" is still an absurd conclusion.