Quote:
Originally Posted by Shub-Nigurrath
Hi all,
The discussion went on for a while, and I saw my name mentioned a few times. To clarify my point, I was saying that AI, before or above everything, is a gigantic tracking tool. It can track what you do with it on an unprecedented scale
So it's better to avoid the risk altogether and switch to a local OSS model, e.g., via Ollama, which is blazing easy, and use Claude or Codex with another model under the hood.
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Thank you
@Shub-Nigurrath
This is one of the main reasons I prefer using local models for reverse engineering is the critical need for privacy. There is a significant body of legal precedent demonstrating how easily law enforcement can obtain chat and usage histories from cloud providers to deanonymize users and link their digital activities to their real-world identities.
For commercial targets, I think abliterated models are the best long-term option. Both the privacy concerns above and the fact that they waste huge numbers of tokens on ineffective attempts make me feel that local LLMs are the better path forward for reversing.
Could you provide some
practical guidance on integrating and utilizing local large language models, such as Qwen 3.8, with IDA Pro and x64dbg?
@squareD, and I have spent the last few days asking for a viable solution; while theoretical frameworks are plentiful, we are struggling to find a
concrete, functional implementation. We are specifically seeking the technical "how-to" and the
practical steps necessary to bridge these tools effectively.
@Fyyre, Thanks for the answer. I intend to explore Grok Build as well, though I will first determine if I can acquire an account anonymously without using a credit card to ensure there is no traceable link to my actual identity. The privacy concerns mentioned by @Shub-Nigurrath are very real.