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Why Johnny Can’t Pentest: An Analysis of Black-Box Web Vulnerability Scanners

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Book cover Detection of Intrusions and Malware, and Vulnerability Assessment (DIMVA 2010)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 6201))

Abstract

Black-box web vulnerability scanners are a class of tools that can be used to identify security issues in web applications. These tools are often marketed as “point-and-click pentesting” tools that automatically evaluate the security of web applications with little or no human support. These tools access a web application in the same way users do, and, therefore, have the advantage of being independent of the particular technology used to implement the web application. However, these tools need to be able to access and test the application’s various components, which are often hidden behind forms, JavaScript-generated links, and Flash applications.

This paper presents an evaluation of eleven black-box web vulnerability scanners, both commercial and open-source. The evaluation composes different types of vulnerabilities with different challenges to the crawling capabilities of the tools. These tests are integrated in a realistic web application. The results of the evaluation show that crawling is a task that is as critical and challenging to the overall ability to detect vulnerabilities as the vulnerability detection techniques themselves, and that many classes of vulnerabilities are completely overlooked by these tools, and thus research is required to improve the automated detection of these flaws.

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Doupé, A., Cova, M., Vigna, G. (2010). Why Johnny Can’t Pentest: An Analysis of Black-Box Web Vulnerability Scanners. In: Kreibich, C., Jahnke, M. (eds) Detection of Intrusions and Malware, and Vulnerability Assessment. DIMVA 2010. Lecture Notes in Computer Science, vol 6201. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14215-4_7

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  • DOI: https://doi.org/10.1007/978-3-642-14215-4_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14214-7

  • Online ISBN: 978-3-642-14215-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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