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POSTER: Seccomp profiling with Dynamic Analysis via ChatGPT-assisted Test Code Generation
- Song, Somin;
- Kundu, Ashish;
- Tak, Byungchul
WEB OF SCIENCE
3SCOPUS
4초록
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
- 제목
- POSTER: Seccomp profiling with Dynamic Analysis via ChatGPT-assisted Test Code Generation
- 저자
- Song, Somin; Kundu, Ashish; Tak, Byungchul
- 발행일
- 2024
- 유형
- Proceedings Paper
- 저널명
- PROCEEDINGS OF THE 19TH ACM ASIA CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY, ACM ASIACCS 2024
- 페이지
- 1928 ~ 1930
- 언어
- ENG
- 출판사
- ASSOC COMPUTING MACHINERY
- 발행국가
- 미국
- 분량
- 3 페이지