HyungSeok Han (KAIST), DongHyeon Oh (KAIST), Sang Kil Cha (KAIST)

JavaScript engines are an attractive target for attackers due to their popularity and flexibility in building exploits. Current state-of-the-art fuzzers for finding JavaScript engine vulnerabilities focus mainly on generating syntactically correct test cases based on either a predefined context-free grammar or a trained probabilistic language model. Unfortunately, syntactically correct JavaScript sentences are often semantically invalid at runtime. Furthermore, statically analyzing the semantics of JavaScript code is challenging due to its dynamic nature: JavaScript code is generated at runtime, and JavaScript expressions are dynamically-typed. To address this challenge, we propose a novel test case generation algorithm that we call semantics-aware assembly, and implement it in a fuzz testing tool termed CodeAlchemist. Our tool can generate arbitrary JavaScript code snippets that are both semantically and syntactically correct, and it effectively yields test cases that can crash JavaScript engines. We found numerous vulnerabilities of the latest JavaScript engines with CodeAlchemist and reported them to the vendors.

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Jinfeng Li (Zhejiang University), Shouling Ji (Zhejiang University), Tianyu Du (Zhejiang University), Bo Li (University of California, Berkeley), Ting Wang (Lehigh University)

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A. Theodore Markettos (University of Cambridge), Colin Rothwell (University of Cambridge), Brett F. Gutstein (Rice University), Allison Pearce (University of Cambridge), Peter G. Neumann (SRI International), Simon W. Moore (University of Cambridge), Robert N. M. Watson (University of Cambridge)

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Tranco: A Research-Oriented Top Sites Ranking Hardened Against Manipulation

Victor Le Pochat (imec-DistriNet, KU Leuven), Tom Van Goethem (imec-DistriNet, KU Leuven), Samaneh Tajalizadehkhoob (Delft University of Technology), Maciej Korczyński (Grenoble Alps University), Wouter Joosen (imec-DistriNet, KU Leuven)

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Cracking the Wall of Confinement: Understanding and Analyzing Malicious...

Eihal Alowaisheq (Indiana University, King Saud University), Peng Wang (Indiana University), Sumayah Alrwais (King Saud University), Xiaojing Liao (Indiana University), XiaoFeng Wang (Indiana University), Tasneem Alowaisheq (Indiana University, King Saud University), Xianghang Mi (Indiana University), Siyuan Tang (Indiana University), Baojun Liu (Tsinghua University)

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