@inproceedings{33fe5aa2421a4e2b97554b8d930eab62,
title = "POSTER: Seccomp profiling with Dynamic Analysis via ChatGPT-assisted Test Code Generation",
abstract = "The effectiveness of Seccomp kernel feature depends on how tightly and accurately the necessary system calls are specified in the seccomp policy. Static code analysis may miss out or over-approximate required system calls. With dynamic analysis, it is difficult to cover all possible execution paths. In this work, we aim to advance the state-of-the-art dynamic analysis approach by enabling it to increase the coverage of the target application{\textquoteright}s functionalities. Our approach takes as input the application{\textquoteright}s online documentation and leverages ChatGPT to generate a large number of test codes for functionalities in the documentation. This automated process eliminates the barrier to manually writing a large number of test codes for conducting dynamic analysis. Through our preliminary evaluation, we confirmed that ChatGPT can be used effectively to automatically generate a large number of test codes. Also, we observed early evidence that the seccomp policy generated from running the test codes could be more sound than the ones generated by static analysis.",
keywords = "ChatGPT, Dynamic analysis, Seccomp, Static analysis, Test code",
author = "Somin Song and Ashish Kundu and Byungchul Tak",
note = "Publisher Copyright: {\textcopyright} 2024 Copyright held by the owner/author(s).; 19th ACM Asia Conference on Computer and Communications Security, AsiaCCS 2024 ; Conference date: 01-07-2024 Through 05-07-2024",
year = "2024",
month = jul,
day = "1",
doi = "10.1145/3634737.3659426",
language = "English",
series = "ACM AsiaCCS 2024 - Proceedings of the 19th ACM Asia Conference on Computer and Communications Security",
publisher = "Association for Computing Machinery, Inc",
pages = "1928--1930",
booktitle = "ACM AsiaCCS 2024 - Proceedings of the 19th ACM Asia Conference on Computer and Communications Security",
}