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Published March 14, 2026 | Version v1
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NanoTag: Systems Support for Efficient Byte-Granular Overflow Detection on ARM MTE (Artifact)

Authors/Creators

  • 1. ROR icon Columbia University
  • 2. University of Pennsylvania

Description

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.

Files

sp26-nanotag-artifact.zip

Files (157.5 MB)

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