Hang Zhang (Indiana University Bloomington), Jangha Kim (The Affiliated Institute of ETRI, ROK), Chuhong Yuan (Georgia Institute of Technology), Zhiyun Qian (University of California, Riverside), Taesoo Kim (Georgia Institute of Technology)

Use-After-Free (UAF) is one of the most widely spread and severe memory safety issues, attracting lots of research efforts toward its automatic discovery. Existing UAF detection approaches include two major categories: dynamic and static. While dynamic methods like fuzzing can detect UAF issues with high precision, they are inherently limited in code coverage. Static approaches, on the other hand, can usually only discover simple sequential UAF cases, despite that many real-world UAF bugs involve intricate cross-entry control and data flows (e.g., concurrent UAFs). Limited static tools supporting cross-entry UAF detection also suffer from inaccuracy or narrowed scope (e.g., cannot handle complex codebases like the Linux kernel).

In this paper, we propose UAFX, a static analyzer capable of discovering cross-entry UAF vulnerabilities in the Linux kernel and potentially extensible to general C programs. UAFX is powered by a novel escape-fetch-based cross-entry alias analysis, enabling it to accurately analyze the alias relationships between the use and free sites even when they scatter in different entry functions. UAFX is also equipped with a systematic UAF validation framework based on partial-order constraints, allowing it to reliably reason about multiple UAF-related code aspects (e.g., locks, path conditions, threads) to filter out false alarms. Our evaluation shows that UAFX can discover new cross-entry UAF vulnerabilities in the kernel and one user-space program (80 true positive warnings), with reasonable reviewer-perceived precision (more than 40%) and performance.

View More Papers

A Key-Driven Framework for Identity-Preserving Face Anonymization

Miaomiao Wang (Shanghai University), Guang Hua (Singapore Institute of Technology), Sheng Li (Fudan University), Guorui Feng (Shanghai University)

Read More

EAGLEYE: Exposing Hidden Web Interfaces in IoT Devices via...

Hangtian Liu (Information Engineering University), Lei Zheng (Institute for Network Sciences and Cyberspace (INSC), Tsinghua University), Shuitao Gan (Laboratory for Advanced Computing and Intelligence Engineering), Chao Zhang (Institute for Network Sciences and Cyberspace (INSC), Tsinghua University), Zicong Gao (Information Engineering University), Hongqi Zhang (Henan Key Laboratory of Information Security), Yishun Zeng (Institute for Network Sciences…

Read More

Exploring User Perceptions of Security Auditing in the Web3...

Molly Zhuangtong Huang (University of Macau), Rui Jiang (University of Macau), Tanusree Sharma (Pennsylvania State University), Kanye Ye Wang (University of Macau)

Read More