Online Q&A fora such as Stack Overflow assist developers to solve their faced coding problems. Despite the advantages, Stack Overflow has the potential to provide insecure code snippets that, if reused, can compromise the security of the entire software. We present Dicos, an accurate approach by examining the change history of Stack Overflow posts for discovering insecure code snippets. When a security issue was detected in a post, the insecure code is fixed to be safe through user discussions, leaving a change history. Inspired by this process, Dicos first extracts the change history from the Stack Overflow post, and then analyzes the history whether it contains security patches, by utilizing pre-selected features that can effectively identify security patches. Finally, when such changes are detected, Dicos determines that the code snippet before applying the security patch is insecure. To evaluate Dicos, we collected 1,958,283 Stack Overflow posts tagged with C, C++, and Android. When we applied Dicos on the collected posts, Dicos discovered 12,458 insecure posts (i.e., 14,719 insecure code snippets) from the collected posts with 91% precision and 93% recall. We further confirmed that the latest versions of 151 out of 2,000 popular C/C++ open-source software contain at least one insecure code snippet taken from Stack Overflow, being discovered by Dicos. Our proposed approach, Dicos, can contribute to preventing further propagation of insecure codes and thus creating a safe code reuse environment.
|Title of host publication
|Proceedings - 37th Annual Computer Security Applications Conference, ACSAC 2021
|Association for Computing Machinery
|Number of pages
|Published - 2021 Dec 6
|37th Annual Computer Security Applications Conference, ACSAC 2021 - Virtual, Online, United States
Duration: 2021 Dec 6 → 2021 Dec 10
|ACM International Conference Proceeding Series
|37th Annual Computer Security Applications Conference, ACSAC 2021
|21/12/6 → 21/12/10
Bibliographical noteFunding Information:
We appreciate the anonymous reviewers and our shepherd for their valuable comments to improve the quality of the paper. We also thank you for the dedicated help of program chairs. This work was supported by Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No.2019-0-01697 Development of Automated Vulnerability Discovery Technologies for Blockchain Platform Security, No.2019-0-01343 Regional Strategic Industry Convergence Security Core Talent Training Business, and No.IITP-2021-2020-0-01819 ICT Creative Consilience program).
© 2021 Association for Computing Machinery.
- Insecure code snippet discovery
- Q&A forum
- Software security
ASJC Scopus subject areas
- Human-Computer Interaction
- Computer Vision and Pattern Recognition
- Computer Networks and Communications