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published_or_final_version / Chemistry / Doctoral / Doctor of Philosophy

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With the rapid proliferation of the internet, web browsers have evolved from single-purpose remote document viewers into multifaceted systems for executing dynamic, interactive web applications. In order to enhance the web browsing experience of users and to facilitate on-demand customizability, most web browsers now can be fitted with extensions: pieces of software that utilize the underlying web platform of a browser and provide a wide range of features such as advertisement blocking, safety ratings of websites, in-browser web development, and many more. Extensible web browsers provide access to their powerful privileged components in order to facilitate the development of feature-rich extensions. This exposure comes at a price, though, as a vulnerable extension can introduce a security hole through which an attacker can access the privileged components and penetrate a victim user’s browser, steal the user’s sensitive information, and even execute arbitrary code in the user’s computer. The current browser security model is inadequate for preventing attacks via such vulnerable extensions. Therefore, an effective protection mechanism is required that would provide web browsers adequate security while still allowing them to be extended. In this thesis, we propose a runtime protection mechanism for JavaScript-based browser extensions. Our protection mechanism performs offline randomization of an extension’s source code and augments the corresponding browser with appropriate modifications. The protection from malicious injection attacks is enforced at runtime by distinguishing attack code from the randomized extension code. Furthermore, for maximum backward compatibility with existing extensions, we propose a complementary static points-to analysis technique that can be invoked on-demand for assessing the security of dynamic code generation functions present in the source code of extensions. Our combined approach of runtime protection and static analysis is independent of the existing extension platforms, thus obviating the need of radically changing the platforms and requiring developers to rewrite their extensions. We implement our protection mechanism in the popular Mozilla Firefox browser and evaluate our approach on a set of vulnerable and non-vulnerable Mozilla Firefox extensions. The evaluation results indicate that our approach can be a viable solution for preventing attacks on JavaScript-based browser extensions while incurring negligible performance overhead and maintaining backward compatibility with existing extensions. / Thesis (Master, Computing) -- Queen's University, 2012-09-27 23:41:46.455

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