Fri 19 Jul 2024 14:00 - 14:18 at Mandacaru - Program Analysis and Performance 3 Chair(s): Shaukat Ali

Nowadays, closed-source software only with stripped binaries still dominates the ecosystem, which brings obstacles to understanding the functionalities of the software and further conducting the security analysis. With such an urgent need, research has traditionally focused on predicting function names, which can only provide fragmented and abbreviated information about functionality. To advance the state-of-the-art, this paper presents Bin2Summary to automatically summarize the functionality of the function in stripped binaries with natural language sentences. Specifically, the proposed framework includes a functionality-specific code embedding module to facilitate fine-grained similarity detection and an attention-based seq2seq model to generate summaries in natural language. Based on 16 widely-used projects (e.g., Coreutils), we have evaluated Bin2Summary with 38,167 functions, which are filtered from 162,406 functions, and all of them have a high-quality comment. Bin2Summary achieves 0.728 in precision and 0.729 in recall on our datasets, and the functionality-specific embedding module can improve the existing assembly language model by up to 109.5% and 109.9% in precision and recall. Meanwhile, the experiments demonstrated that Bin2Summary has outstanding transferability in analyzing the cross-architecture (i.e., in x64 and x86) and cross-environment (i.e., in Cygwin and MSYS2) binaries. Finally, the case study illustrates how Bin2Summary outperforms the existing works in providing functionality summaries with abundant semantics beyond function names.

Fri 19 Jul

Displayed time zone: Brasilia, Distrito Federal, Brazil change

14:00 - 15:30
Program Analysis and Performance 3Research Papers at Mandacaru
Chair(s): Shaukat Ali Simula Research Laboratory and Oslo Metropolitan University
14:00
18m
Talk
Bin2Summary: Beyond Function Name Prediction in Stripped Binaries with Functionality-specific Code Embeddings
Research Papers
Zirui Song The Chinese University of Hong Kong, Jiongyi Chen National University of Defense Technology, Kehuan Zhang The Chinese University of Hong Kong
14:18
18m
Talk
Active Monitoring Mechanism for Control-based Self-Adaptive Systems
Research Papers
Yi Qin State Key Laboratory for Novel Software Technology, Nanjing University, Yanxiang Tong State Key Laboratory for Novel Software Technology, Nanjing University, Yifei Xu State Key Laboratory for Novel Software Technology, Nanjing University, Chun Cao State Key Laboratory for Novel Software Technology, Nanjing University, Xiaoxing Ma State Key Laboratory for Novel Software Technology, Nanjing University
14:36
18m
Talk
Cut to the Chase: An Error-Oriented Approach to Detect Error-Handling Bugs
Research Papers
Haoran Liu National University of Defense Technology, Zhouyang Jia National University of Defense Technology, Shanshan Li National University of Defense Technology, Yan Lei Chongqing University, Yue Yu National University of Defense Technology, Yu Jiang Tsinghua university, Xiaoguang Mao National University of Defense Technology, Liao Xiangke National University of Defense Technology
14:54
18m
Talk
DAInfer: Inferring API Aliasing Specifications from Library Documentation via Neurosymbolic Optimization
Research Papers
Chengpeng Wang The Hong Kong University of Science and Technology, Jipeng Zhang The Hong Kong University of Science and Technology, Rongxin Wu School of Informatics, Xiamen University, Charles Zhang The Hong Kong University of Science and Technology
15:12
18m
Talk
Decomposing Software Verification Using Distributed Summary Synthesis
Research Papers
Dirk Beyer LMU Munich, Matthias Kettl LMU Munich, Thomas Lemberger LMU Munich
DOI Media Attached File Attached