SafePyScript: A Web-Based Solution for Machine Learning-Driven Vulnerability Detection in Python
Talaya Farasat, Atiqullah Ahmadzai, Aleena Elsa George, Sayed Alisina, Qaderi, Dusan Dordevic, Joachim Posegga

TL;DR
SafePyScript is a web-based machine learning tool that helps Python developers easily detect vulnerabilities in their source code, addressing a critical gap in cybersecurity tools for Python programming.
Contribution
This paper introduces SafePyScript, the first accessible web application leveraging machine learning to identify vulnerabilities in Python source code.
Findings
Provides an easy-to-use web interface for vulnerability detection
Utilizes machine learning models trained on Python vulnerability datasets
Enhances Python security with a convenient detection tool
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/
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComputational Physics and Python Applications
