POSTER: Seccomp profiling with Dynamic Analysis via ChatGPT-assisted Test Code Generation

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3
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4

초록

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's functionalities. Our approach takes as input the application'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.

키워드

Seccomp; ChatGPT; Static analysis; Dynamic analysis; Test code
제목
POSTER: Seccomp profiling with Dynamic Analysis via ChatGPT-assisted Test Code Generation
저자
Song, Somin; Kundu, Ashish; Tak, Byungchul
DOI
10.1145/3634737.3659426
발행일
2024
유형
Proceedings Paper
저널명
PROCEEDINGS OF THE 19TH ACM ASIA CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY, ACM ASIACCS 2024
페이지
1928 ~ 1930