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.

View More Papers

BadBluetooth: Breaking Android Security Mechanisms via Malicious Bluetooth Peripherals

Fenghao Xu (The Chinese University of Hong Kong), Wenrui Diao (Jinan University), Zhou Li (University of California, Irvine), Jiongyi Chen (The Chinese University of Hong Kong), Kehuan Zhang (The Chinese University of Hong Kong)

Read More

Don't Trust The Locals: Investigating the Prevalence of Persistent...

Marius Steffens (CISPA Helmholtz Center for Information Security), Christian Rossow (CISPA Helmholtz Center for Information Security), Martin Johns (TU Braunschweig), Ben Stock (CISPA Helmholtz Center for Information Security)

Read More

Latex Gloves: Protecting Browser Extensions from Probing and Revelation...

Alexander Sjösten (Chalmers University of Technology), Steven Van Acker (Chalmers University of Technology), Pablo Picazo-Sanchez (Chalmers University of Technology), Andrei Sabelfeld (Chalmers University of Technology)

Read More

Analyzing Semantic Correctness with Symbolic Execution: A Case Study...

Sze Yiu Chau (Purdue University), Moosa Yahyazadeh (The University of Iowa), Omar Chowdhury (The University of Iowa), Aniket Kate (Purdue University), Ninghui Li (Purdue University)

Read More