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

Power-Related Side-Channel Attacks using the Android Sensor Framework

Mathias Oberhuber (Graz University of Technology), Martin Unterguggenberger (Graz University of Technology), Lukas Maar (Graz University of Technology), Andreas Kogler (Graz University of Technology), Stefan Mangard (Graz University of Technology)

Read More

Transparency or Information Overload? Evaluating Users’ Comprehension and Perceptions...

Xiaoyuan Wu (Carnegie Mellon University), Lydia Hu (Carnegie Mellon University), Eric Zeng (Carnegie Mellon University), Hana Habib (Carnegie Mellon University), Lujo Bauer (Carnegie Mellon University)

Read More

No Source Code? No Problem! Twenty Years of Research...

Jack W. Davidson, Professor of Computer Science in the School of Engineering and Applied Science, University of Virginia

Read More