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SOK: On the Analysis of Web Browser Security

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arxiv 2112.15561 v1 pith:Z6VPINCJ submitted 2021-12-31 cs.CR

SOK: On the Analysis of Web Browser Security

classification cs.CR
keywords browserssecuritybrowsercomplexmoderntechniquesbugscode
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Web browsers are integral parts of everyone's daily life. They are commonly used for security-critical and privacy sensitive tasks, like banking transactions and checking medical records. Unfortunately, modern web browsers are too complex to be bug free (e.g., 25 million lines of code in Chrome), and their role as an interface to the cyberspace makes them an attractive target for attacks. Accordingly, web browsers naturally become an arena for demonstrating advanced exploitation techniques by attackers and state-of-the-art defenses by browser vendors. Web browsers, arguably, are the most exciting place to learn the latest security issues and techniques, but remain as a black art to most security researchers because of their fast-changing characteristics and complex code bases. To bridge this gap, this paper attempts to systematize the security landscape of modern web browsers by studying the popular classes of security bugs, their exploitation techniques, and deployed defenses. More specifically, we first introduce a unified architecture that faithfully represents the security design of four major web browsers. Second, we share insights from a 10-year longitudinal study on browser bugs. Third, we present a timeline and context of mitigation schemes and their effectiveness. Fourth, we share our lessons from a full-chain exploit used in 2020 Pwn2Own competition. and the implication of bug bounty programs to web browser security. We believe that the key takeaways from this systematization can shed light on how to advance the status quo of modern web browsers, and, importantly, how to create secure yet complex software in the future.

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    Agentic browsers are vulnerable to 20 web and LLM attacks with 18 implemented, exposing five failure modes across four major LLM models that require redesign before safe deployment.