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      An Empirical Analysis of Vulnerabilities in Python Packages for Web Applications

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          Abstract

          This paper examines software vulnerabilities in common Python packages used particularly for web development. The empirical dataset is based on the PyPI package repository and the so-called Safety DB used to track vulnerabilities in selected packages within the repository. The methodological approach builds on a release-based time series analysis of the conditional probabilities for the releases of the packages to be vulnerable. According to the results, many of the Python vulnerabilities observed seem to be only modestly severe; input validation and cross-site scripting have been the most typical vulnerabilities. In terms of the time series analysis based on the release histories, only the recent past is observed to be relevant for statistical predictions; the classical Markov property holds.

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          Predicting U.S. Recessions with Dynamic Binary Response Models

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              On the impact of security vulnerabilities in the npm package dependency network

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                Author and article information

                Journal
                31 October 2018
                Article
                1810.13310
                dc06c375-e7e0-494a-b4c6-8c46143045e4

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                Forthcoming in: Proceedings of the 9th International Workshop on Empirical Software Engineering in Practice (IWESEP 2018), Nara, IEEE
                cs.SE cs.CR

                Software engineering,Security & Cryptology
                Software engineering, Security & Cryptology

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