25 million flows later: large-scale detection of DOM-based XSS

  • Authors:
  • Sebastian Lekies;Ben Stock;Martin Johns

  • Affiliations:
  • SAP AG, Karlsruhe, Germany;Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen-Nuremberg, Germany;SAP AG, Karlsruhe, Germany

  • Venue:
  • Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security
  • Year:
  • 2013

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Abstract

In recent years, the Web witnessed a move towards sophis- ticated client-side functionality. This shift caused a signifi- cant increase in complexity of deployed JavaScript code and thus, a proportional growth in potential client-side vulnera- bilities, with DOM-based Cross-site Scripting being a high impact representative of such security issues. In this paper, we present a fully automated system to detect and validate DOM-based XSS vulnerabilities, consisting of a taint-aware JavaScript engine and corresponding DOM implementation as well as a context-sensitive exploit generation approach. Using these components, we conducted a large-scale analysis of the Alexa top 5000. In this study, we identified 6167 unique vulnerabilities distributed over 480 domains, show- ing that 9,6% of the examined sites carry at least one DOM- based XSS problem.