Plankton: Reconciling Binary Code and Debug Information

Anshunkang Zhou, Chengfeng Ye, Heqing Huang*, Yuandao Cai, Charles Zhang

*Corresponding author for this work

Research output: Chapter in Book/Conference Proceeding/ReportConference Paper published in a bookpeer-review

Abstract

Static analysis has been widely used in large-scale software defect detection. Despite recent advances, it is still not practical enough because it requires compilation interference to obtain analyzable code. Directly translating the binary code using a binary lifter mitigates this practicality problem by being non-intrusive to the building system. However, existing binary lifters cannot produce precise enough code for rigorous static analysis even in the presence of the debug information. In this paper, 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 full-fledged static analysis with minor precision loss. Plankton shows comparable static analysis results with traditional compilation interference solutions, producing only 17.2% differences while being much more practical, outperforming existing lifters by 76.9% on average.

Original languageEnglish
Title of host publicationSummer Cycle
PublisherAssociation for Computing Machinery
Pages912-928
Number of pages17
ISBN (Electronic)9798400703850
DOIs
Publication statusPublished - 27 Apr 2024
Event29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2024 - San Diego, United States
Duration: 27 Apr 20241 May 2024

Publication series

NameInternational Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS
Volume2

Conference

Conference29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2024
Country/TerritoryUnited States
CitySan Diego
Period27/04/241/05/24

Bibliographical note

Publisher Copyright:
© 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

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