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

Cascading Spy Sheets: Exploiting the Complexity of Modern CSS...

Leon Trampert (CISPA Helmholtz Center for Information Security), Daniel Weber (CISPA Helmholtz Center for Information Security), Lukas Gerlach (CISPA Helmholtz Center for Information Security), Christian Rossow (CISPA Helmholtz Center for Information Security), Michael Schwarz (CISPA Helmholtz Center for Information Security)

Read More

Unleashing the Power of Generative Model in Recovering Variable...

Xiangzhe Xu (Purdue University), Zhuo Zhang (Purdue University), Zian Su (Purdue University), Ziyang Huang (Purdue University), Shiwei Feng (Purdue University), Yapeng Ye (Purdue University), Nan Jiang (Purdue University), Danning Xie (Purdue University), Siyuan Cheng (Purdue University), Lin Tan (Purdue University), Xiangyu Zhang (Purdue University)

Read More

Vision: Comparison of AI-assisted Policy Development Between Professionals and...

Rishika Thorat (Purdue University), Tatiana Ringenberg (Purdue University)

Read More

Interventional Root Cause Analysis of Failures in Multi-Sensor Fusion...

Shuguang Wang (City University of Hong Kong), Qian Zhou (City University of Hong Kong), Kui Wu (University of Victoria), Jinghuai Deng (City University of Hong Kong), Dapeng Wu (City University of Hong Kong), Wei-Bin Lee (Information Security Center, Hon Hai Research Institute), Jianping Wang (City University of Hong Kong)

Read More