NanoTag: Systems Support for Efficient Byte-Granular Overflow Detection on ARM MTE (Artifact)
Li, Mingkai; Ye, Hang; Devietti, Joseph; Jana, Suman; Khan, Tanvir Ahmed;
NanoTag: Systems Support for Efficient Byte-Granular Overflow Detection on ARM MTE (Artifact)
This is the artifact for the paper NanoTag: Systems Support for Efficient Byte-Granular Overflow Detection on ARM MTE in S&P 2026. The latest artifact can be found here: https://github.com/ice-rlab/nanotag. This artifact NanoTag is a system to efficiently detect memory safety bugs probabilistically in unmodified MTE-enabled binaries at byte granularity, addressing intra-granule buffer overflows in real hardware to help in-house testing (e.g., fuzzing) detect such bugs with an explicit detection-performance tradeoff.
- King’s University United States
- University of Pennsylvania United States
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selected citations
Citations provided by BIP!
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Citations provided by BIP!popularityPopularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
Popularity provided by BIP! 0
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Average