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Towards Industrial-Scale Software Binary Analysis
PhD Thesis Proposal Defence Title: "Towards Industrial-Scale Software Binary Analysis" by Mr. Anshunkang ZHOU Abstract: Software binaries form the operational backbone of modern industrial systems, from critical infrastructure and medical devices to autonomous vehicles and IoT ecosystems. However, vulnerabilities in these binaries, such as memory corruption and logic errors, pose significant risks, including catastrophic safety failures and financial losses. Traditional methods for ensuring the safety of industrial software require access to source code and interference with the building process to obtain analyzable artifacts (e.g., intermediate representations). Those approaches are impractical and imprecise in industrial-scale environments due to the complexity of modern building systems and the widespread usage of third-party libraries. This proposal introduces two key techniques for industrial-scale software binary analysis to overcome the above limitations. First, we propose a new binary lifter Plankton together with two new algorithms that can fill the gaps between the low- and high-level code to produce high-quality LLVM intermediate representations (IRs) from binaries with debug information, enabling non-intrusive full-fledged static analysis with minor precision loss. Second, we propose Arcturus, a new binary similarity analysis technique that can achieve high code coverage and high accuracy simultaneously by manipulating program execution under the guidance of code reachability. Our method has already demonstrated real-world impact by deploying to industrial environments and identifying critical vulnerabilities in widely used systems. Date: Tuesday, 27 May 2025 Time: 10:00am - 12:00noon Venue: Room 2128A Lift 19 Committee Members: Prof. Charles Zhang (Supervisor) Dr. Shuai Wang (Chairperson) Dr. Dongdong She