We propose a methodology to leverage machine learning (ML) for the detection of web application vulnerabilities. We use it in the design of Mitch, the first ML solution for the black-box detection of cross-site request forgery vulnerabilities. Finally, we show the effectiveness of Mitch on real software.

Machine Learning for Web Vulnerability Detection: The Case of Cross-Site Request Forgery

Calzavara S.;Focardi R.;Rabitti A.;
2020

Abstract

We propose a methodology to leverage machine learning (ML) for the detection of web application vulnerabilities. We use it in the design of Mitch, the first ML solution for the black-box detection of cross-site request forgery vulnerabilities. Finally, we show the effectiveness of Mitch on real software.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10278/3729046
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