Automating Static Code Analysis Through CI/CD Pipeline Integration


연구 분야: Verification



학회: 2024 IEEE International Conference on Software Analysis, Evolution and Reengineering - Companion (SANER-C)


초록

In the contemporary landscape of software devel-opment, securing sensitive data is paramount to safeguarding organizational reputation, preventing financial losses, and pro-tecting individuals from identity theft. This paper addresses the pervasive challenge of identifying and rectifying security vulnerabilities early in the development process, emphasizing the role of Static Application Security Testing (SAST) tools. While SAST tools play a crucial role in detecting vulnerabilities, widespread adoption has been hindered by usability issues, including high false positive rates and a lack of native pipeline support. This paper proposes a novel, generalized, and automated process for aggregating SAST tool outputs and integrating them into developers' familiar issue-tracking software. The process streamlines the identification and communication of security vulnerabilities during the development lifecycle, facilitating more efficient remediation efforts. We demonstrate the successful implementation of the proposed process with the SonarQube SAST tool in a GitLab-based development environment. Developers were positive about the structured implementation, real-time feedback, and proactive vulnerability management. However, despite some challenges such as a potential learning curve and tradeoffs between secure coding and workflow disruption, the overall positive impact on security awareness and responsiveness suggests that the proposed process holds promise in enhancing the security posture of software development practices


Author Profile
Ann Marie Reinhold

Gianforte School of Computing Montana State University Bozeman Montana USA

United States
Author Profile
Zachary Wadhams

Gianforte School of Computing Montana State University Bozeman Montana USA

United States
Author Profile
Clemente Izurieta

Gianforte School of Computing Montana State University Pacific Northwest National Laboratory Idaho National Laboratory Bozeman Montana USA

United States

📄 논문 정보

발행 연도 2024년
인용수 5
출판 국가 United States
사이트 IEEE
좋아요 수 0

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