为什么在人工智能时代反编译仍然不是一个解决的问题？
有成千上万对源代码与可执行文件的组合可以用于训练，而编译器是一个参数，AI可以轻松识别并将其视为一个重要因素。那么，为什么没有（或者可能有，但我不知道）基于AI的反编译器，可以将几乎任何机器代码转换为高度可读的源代码（并且包含对变量名称和注释的有意义猜测）呢？当可执行文件可以在运行时被AI模型运行和检查时，这似乎应该更容易。
目前AI反编译的技术水平如何？有没有我可以今天就能使用的工具？
查看原文
There are thousands of pairs of source-executable pairs that could be used for training, and the compiler is a parameter that AI can easily identify and account for as a heavily weighted factor.<p>So why isn't there (or maybe there is and I don't know about it) an AI based decompiler that can take almost any machine code, and transform it into highly readable source code (complete with meaningful guesses for variable names and comments)? It seems like it should be even easier when the executable could be run and inspected at runtime by the AI model.<p>What is the state of the art with AI decompilation, and are there tools I can play with today?