Source Code Vulnerability Detection Using Static Analysis and Pattern Matching

Abstract

In the rapidly evolving field of web development, ensuring the security of web applications is paramount. Most of the vulnerabilities occur due to lack of best practices during coding. Traditional security testing methods, which are predominantly reactive, tend to identify vulnerabilities in source code only after substantial portions of the application have been developed. This reactive approach significantly increases the complexity and cost of mitigating security risks. This research addresses this challenge by integrating security directly into the development process through a VS (Visual Studio) Code Extension by performing a real-time Static Analysis of source code to detect vulnerabilities which are written using JavaScript language. The tool can identify common security vulnerabilities such as SQL Injection (SQLi), Cross-Site Scripting (XSS), Cross-Site Request Forgery (CSRF) using the pattern matching techniques of static analysis. By integrating the tool directly into VS Code, it can provide developers with immediate feedback on security risks. The tool is not only useful for identifying vulnerabilities but also enhances the developer’s overall coding practices. The integration of the tool into the development environment will reduce time and resources spent on post- development security testing. In conclusion, this tool represents a significant step forward in the effort to embed security within the software development lifecycle. Its development and deployment will underscore the effectiveness of proactive security practices, offering a model that could be replicated and extended to other development environments and programming languages.

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Pitiyegedara, J.D.; Nishshanka, I.S.B. (2024) Source Code Vulnerability Detection Using Static Analysis and Pattern Matching, International Conference on Advanced Computing Technologies (ICACT), NSBM Green University, Sri Lanka. P.167-172

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