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

Countering Malicious Processes with Process-DNS Association

Suphannee Sivakorn (Columbia University), Kangkook Jee (NEC Labs America), Yixin Sun (Princeton University), Lauri Korts-Pärn (Cyber Defense Institute), Zhichun Li (NEC Labs America), Cristian Lumezanu (NEC Labs America), Zhenyu Wu (NEC Labs America), Lu-An Tang (NEC Labs America), Ding Li (NEC Labs America)

Read More

Digital Healthcare-Associated Infection: A Case Study on the Security...

Luis Vargas (University of Florida), Logan Blue (University of Florida), Vanessa Frost (University of Florida), Christopher Patton (University of Florida), Nolen Scaife (University of Florida), Kevin R.B. Butler (University of Florida), Patrick Traynor (University of Florida)

Read More

Data Oblivious ISA Extensions for Side Channel-Resistant and High...

Jiyong Yu (UIUC), Lucas Hsiung (UIUC), Mohamad El'Hajj (UIUC), Christopher W. Fletcher (UIUC)

Read More

Unveiling your keystrokes: A Cache-based Side-channel Attack on Graphics...

Daimeng Wang (University of California Riverside), Ajaya Neupane (University of California Riverside), Zhiyun Qian (University of California Riverside), Nael Abu-Ghazaleh (University of California Riverside), Srikanth V. Krishnamurthy (University of California Riverside), Edward J. M. Colbert (Virginia Tech), Paul Yu (U.S. Army Research Lab (ARL))

Read More