SafePyScript: A Web-Based Solution for Machine Learning-Driven Vulnerability Detection in Python
Year: 2024
Type: preprint
Abstract: Software vulnerabilities are a fundamental cause of cyber attacks. Effectively identifying these vulnerabilities is essential for robust cybersecurity, yet it remains a complex and challenging task. In this paper, we present SafePyScript, a machine learning-based web application designed specifically to identify vulnerabilities in Python source code. Despite Python's significance as a major programming language, there is currently no convenient and easy-to-use machine learning-based web application for detecting vulnerabilities in its source code. SafePyScript addresses this gap by providing an accessible solution for Python programmers to ensure the security of their applications. SafePyScript link: https://safepyscript.com/
Source: arXiv (Cornell University)
Authors: Farasat, Talaya, Ahmadzai, Atiqullah, George, Aleena Elsa, Qaderi, Sayed Alisina, Dordevic, Dusan, Posegga, Joachim
Institution: University of Passau
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4404345305