Enhancing Black-box Compiler Option Fuzzing with LLM through Command Feedback

Since the compiler acts as a core component in software building, it is essential to ensure its availability and reliability through software testing and security analysis. Most research has focused on compiler robustness when compiling various test cases, while the reliability of compiler options lacks attention, especially since each option can activate a specific compiler function. Although some researchers have made efforts in testing it, the insufficient utilization of compiler command feedback messages leads to the poor efficiency, which hinders more diverse and in-depth testing.In this paper, we propose a novel solution to enhance black-box compiler option fuzzing by utilizing command feedback, such as error messages, standard output and compiled files, to guide the error fixing and option pruning via prompting large language models for suggestions. We have implemented the prototype and evaluated it on 4 versions of LLVM. Experiments show that our method significantly improves the detection of crashes, reduces false negatives, and even increase the success rate of compilation when compared to the baseline. To date, our method has identified hundreds of unique bugs, and 9 of them are previously unknown. Among these, 8 have been assigned CVE numbers, and 1 has been fixed following our report.

Authors

Publication Details

Published
2024-10-28
DOI
https://doi.org/10.1109/issre62328.2024.00039
Citations
4
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
1.96
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article

Enhancing Black-box Compiler Option Fuzzing with LLM through Command Feedback

Zulie Pan, Huimin Ma, Lu Yu, Taiyan Wang et al.
4 citations
Parallel Computing and Optimization Techniques
1.96
article

Enhancing Black-box Compiler Option Fuzzing with LLM through Command Feedback

Zulie Pan, Huimin Ma, Lu Yu, Taiyan Wang, Ruipeng Wang, Jinghua Zheng, Yu Chen, Min Zhang
article en
4 citations

Abstract

Since the compiler acts as a core component in software building, it is essential to ensure its availability and reliability through software testing and security analysis. Most research has focused on compiler robustness when compiling various test cases, while the reliability of compiler options lacks attention, especially since each option can activate a specific compiler function. Although some researchers have made efforts in testing it, the insufficient utilization of compiler command feedback messages leads to the poor efficiency, which hinders more diverse and in-depth testing.In this paper, we propose a novel solution to enhance black-box compiler option fuzzing by utilizing command feedback, such as error messages, standard output and compiled files, to guide the error fixing and option pruning via prompting large language models for suggestions. We have implemented the prototype and evaluated it on 4 versions of LLVM. Experiments show that our method significantly improves the detection of crashes, reduces false negatives, and even increase the success rate of compilation when compared to the baseline. To date, our method has identified hundreds of unique bugs, and 9 of them are previously unknown. Among these, 8 have been assigned CVE numbers, and 1 has been fixed following our report.

Openalex Percentile: Top 12%
Parallel Computing and Optimization Techniques
1.96
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Enhancing Black-box Compiler Option Fuzzing with LLM through Command Feedback — Zulie Pan, Huimin Ma, et al. · (2024) | TGRS Research Map | TGRS