GIANTSAN: Efficient Memory Sanitization with Segment Folding

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review

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Detail(s)

Original languageEnglish
Title of host publicationACM Conference on Architectural Support for Programming Languages and Operating Systems
Number of pages16
Publication statusPublished - Apr 2024

Conference

Title29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS 2024)
Location
PlaceUnited States
CitySan Diego
Period27 April - 1 May 2024

Abstract

Memory safety sanitizers, the sharp weapon for detecting invalid memory operations during execution, employ runtime metadata to model the memory and help find memory errors hidden in the programs. However, location-based methods, the most widely deployed memory sanitization methods thanks to their high compatibility, face the low protection density issue: the number of bytes safeguarded by one metadata is limited. As a result, numerous memory accesses require loading excessive metadata, leading to a high runtime overhead. To address this issue, we propose a new shadow encoding with segment folding to increase the protection density. Specifically, we characterize neighboring bytes with identical metadata by building novel summaries, called folded segments, on those bytes to reduce unnecessary metadata loadings. The new encoding uses less metadata to safeguard large memory regions, speeding up memory sanitization. We implement our designed technique as GIANTSAN. Our evaluation using the SPEC CPU 2017 benchmark shows that GIANTSAN outperforms the state-of-the-art methods with 59.10% and 38.52% less runtime overhead than ASan and ASan--, respectively. Moreover, under the same redzone setting, GIANTSAN detects 463 fewer false negative cases than ASan and ASan-- in testing the real-world project PHP.

Bibliographic Note

Information for this record is supplemented by the author(s) concerned. Since this conference is yet to commence, the information for this record is subject to revision.

Citation Format(s)

GIANTSAN: Efficient Memory Sanitization with Segment Folding. / Ling, Hao; Huang, Heqing; Wang, Chengpeng et al.
ACM Conference on Architectural Support for Programming Languages and Operating Systems. 2024.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review