Exploring Automated Vulnerability Identification in JavaScript Code Using Large Language Models
JavaScript powers approximately 98.8% of all websites, making vulnerabilities in its code a significant security risk, yet existing detection approaches such as Static Application Security Testing (SAST) tools often fail to identify many real-world vulnerabilities when applied to isolated code snippets. This paper pres...
Manit Kaushik, Ishir Bhardwaj, Pranav Gupta et al.
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