LSAFE: a Lightweight Static Analysis Framework for binary Executables

Conference · Mon Sep 09 04:00:00 EDT 2024

OSTI ID:2446860

Qu, Guangzhi ^[1]; Yue, Xiao

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1. Automation Alley

Static analysis is a widely used technique for analyzing various aspects of programs. However, as programs become more complex, static analysis tools require larger resources, such as CPU time and memory, to perform the same tasks. Moreover, the source code of programs may not always be accessible, requiring static analysis to be performed on the binary executable code directly. To overcome these challenges, we propose a lightweight static analysis framework called LSAFE, which constructs control flow graphs (CFGs) and data dependency graphs (DDGs) of target programs with optimized performance in terms of CPU and memory usage. We evaluated the proposed framework using both Spec benchmark programs and real-world industrial applications, and found that it outperformed Angr, an existing state-of-the-art static analysis tool. Additionally, we demonstrate a case study that utilizes the CFG generated by LSAFE to detect memory leaks.

• Research Organization: Oakland University
• Sponsoring Organization: USDOE Office of Cybersecurity, Energy Security, and Emergency Response (CESER)
• DOE Contract Number: CR0000023
• OSTI ID: 2446860
• Report Number(s): DOE-Oakland University-0000023
• Country of Publication: United States
• Language: English