CRApr 10, 2017

Leveraging Flawed Tutorials for Seeding Large-Scale Web Vulnerability Discovery

arXiv:1704.02786v119 citationsHas Code
AI Analysis

This addresses the issue of insecure open-source software for developers and security researchers, though it is incremental in applying known methods to new data.

The study tackled the problem of security vulnerabilities in web tutorials by analyzing 64,415 PHP codebases on GitHub, finding 117 vulnerabilities with strong syntactic similarity to flawed tutorial snippets.

The Web is replete with tutorial-style content on how to accomplish programming tasks. Unfortunately, even top-ranked tutorials suffer from severe security vulnerabilities, such as cross-site scripting (XSS), and SQL injection (SQLi). Assuming that these tutorials influence real-world software development, we hypothesize that code snippets from popular tutorials can be used to bootstrap vulnerability discovery at scale. To validate our hypothesis, we propose a semi-automated approach to find recurring vulnerabilities starting from a handful of top-ranked tutorials that contain vulnerable code snippets. We evaluate our approach by performing an analysis of tens of thousands of open-source web applications to check if vulnerabilities originating in the selected tutorials recur. Our analysis framework has been running on a standard PC, analyzed 64,415 PHP codebases hosted on GitHub thus far, and found a total of 117 vulnerabilities that have a strong syntactic similarity to vulnerable code snippets present in popular tutorials. In addition to shedding light on the anecdotal belief that programmers reuse web tutorial code in an ad hoc manner, our study finds disconcerting evidence of insufficiently reviewed tutorials compromising the security of open-source projects. Moreover, our findings testify to the feasibility of large-scale vulnerability discovery using poorly written tutorials as a starting point.

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