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Proceedings of ACM on programming languages, 2023-06, Vol.7 (PLDI), p.907-927, Article 143
2023

Details

Autor(en) / Beteiligte
Titel
Don’t Look UB: Exposing Sanitizer-Eliding Compiler Optimizations
Ist Teil von
  • Proceedings of ACM on programming languages, 2023-06, Vol.7 (PLDI), p.907-927, Article 143
Ort / Verlag
New York, NY, USA: ACM
Erscheinungsjahr
2023
Link zum Volltext
Quelle
ACM Digital Library
Beschreibungen/Notizen
  • Sanitizers are widely used compiler features that detect undefined behavior and resulting vulnerabilities by injecting runtime checks into programs. For better performance, sanitizers are often used in conjunction with optimization passes. But doing so combines two compiler features with conflicting objectives. While sanitizers want to expose undefined behavior, optimizers often exploit these same properties for performance. In this paper, we show that this clash can have serious consequences: optimizations can remove sanitizer failures, thereby hiding the presence of bugs or even introducing new ones. We present LookUB, a differential-testing based framework for finding optimizer transformations that elide sanitizer failures. We used our method to find 17 such sanitizer-eliding optimizations in Clang. Next, we used static analysis and fuzzing to search for bugs in open-source projects that were previously hidden due to sanitizer-eliding optimizations. This led us to discover 20 new bugs in Linux Containers, libmpeg2, NTFS-3G, and WINE. Finally, we present an effective mitigation strategy based on a customization of the Clang optimizer with an overhead increase of 4%.
Sprache
Englisch
Identifikatoren
ISSN: 2475-1421
eISSN: 2475-1421
DOI: 10.1145/3591257
Titel-ID: cdi_crossref_primary_10_1145_3591257

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