--- language: code # <-- my language widget: - text: "# This is the assembly code with O0 optimization:\n:\nendbr64\nlea (%rdi,%rsi,1),%eax\nretq\n# What is the source code?\n" license: other tags: - decompile - binary --- ### 1. Introduction of LLM4Decompile LLM4Decompile aims to decompile x86 assembly instructions into C. It is finetuned from Deepseek-Coder on 4B tokens of assembly-C pairs compiled from AnghaBench. - **Github Repository:** [LLM4Decompile](https://github.com/albertan017/LLM4Decompile) - **Paper link:** For more details check out the [paper](https://arxiv.org/abs/2403.05286). ### 2. Evaluation Results | Model | Re-compilability | | | | | Re-executability | | | | | |--------------------|:----------------:|:---------:|:---------:|:---------:|:---------:|:----------------:|-----------|-----------|-----------|:---------:| | Optimization-level | O0 | O1 | O2 | O3 | Avg. | O0 | O1 | O2 | O3 | Avg. | | GPT4 | 0.92 | 0.94 | 0.88 | 0.84 | 0.895 | 0.1341 | 0.1890 | 0.1524 | 0.0854 | 0.1402 | | DeepSeek-Coder-33B | 0.0659 | 0.0866 | 0.1500 | 0.1463 | 0.1122 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | | LLM4Decompile-1b | 0.8780 | 0.8732 | 0.8683 | 0.8378 | 0.8643 | 0.1573 | 0.0768 | 0.1000 | 0.0878 | 0.1055 | | LLM4Decompile-6b | 0.8817 | 0.8951 | 0.8671 | 0.8476 | 0.8729 | 0.3000 | 0.1732 | 0.1988 | 0.1841 | 0.2140 | | LLM4Decompile-33b | 0.8134 | 0.8195 | 0.8183 | 0.8305 | 0.8204 | 0.3049 | 0.1902 | 0.1817 | 0.1817 | 0.2146 | ### 3. How to Use Here give an example of how to use our model. First compile the C code into binary, disassemble the binary into assembly instructions: ```python import subprocess import os import re digit_pattern = r'\b0x[a-fA-F0-9]+\b'# binary codes in Hexadecimal zeros_pattern = r'^0+\s'#0s OPT = ["O0", "O1", "O2", "O3"] fileName = 'path/to/file' with open(fileName+'.c','r') as f:#original file c_func = f.read() for opt_state in OPT: output_file = fileName +'_' + opt_state input_file = fileName+'.c' compile_command = f'gcc -c -o {output_file}.o {input_file} -{opt_state} -lm'#compile the code with GCC on Linux subprocess.run(compile_command, shell=True, check=True) compile_command = f'objdump -d {output_file}.o > {output_file}.s'#disassemble the binary file into assembly instructions subprocess.run(compile_command, shell=True, check=True) input_asm = '' with open(output_file+'.s') as f:#asm file asm= f.read() asm = asm.split('Disassembly of section .text:')[-1].strip() for tmp in asm.split('\n'): tmp_asm = tmp.split('\t')[-1]#remove the binary code tmp_asm = tmp_asm.split('#')[0].strip()#remove the comments input_asm+=tmp_asm+'\n' input_asm = re.sub(zeros_pattern, '', input_asm) before = f"# This is the assembly code with {opt_state} optimization:\n"#prompt after = "\n# What is the source code?\n"#prompt input_asm_prompt = before+input_asm.strip()+after with open(fileName +'_' + opt_state +'.asm','w',encoding='utf-8') as f: f.write(input_asm_prompt) ``` Then use LLM4Decompile to translate the assembly instructions into C: ```python from transformers import AutoTokenizer, AutoModelForCausalLM import torch model_path = 'arise-sustech/llm4decompile-1.3b' tokenizer = AutoTokenizer.from_pretrained(model_path) model = AutoModelForCausalLM.from_pretrained(model_path,torch_dtype=torch.bfloat16).cuda() with open(fileName +'_' + opt_state +'.asm','r') as f:#original file asm_func = f.read() inputs = tokenizer(asm_func, return_tensors="pt").to(model.device) with torch.no_grad(): outputs = model.generate(**inputs, max_new_tokens=512) c_func_decompile = tokenizer.decode(outputs[0][len(inputs[0]):-1]) ``` ### 4. License This code repository is licensed under the DeepSeek License. ### 5. Contact If you have any questions, please raise an issue. ### 6. Citation ``` @misc{tan2024llm4decompile, title={LLM4Decompile: Decompiling Binary Code with Large Language Models}, author={Hanzhuo Tan and Qi Luo and Jing Li and Yuqun Zhang}, year={2024}, eprint={2403.05286}, archivePrefix={arXiv}, primaryClass={cs.PL} } ```