Dataset and Reproducibility for ReSect: A Tool for Automated Analysis of Reentrancy Transactions on Blockchains

This dataset accompanies ReSect, a tool for automated post-mortem analysis of reentrancy transactions on EVM-compatible blockchains. It contains two PostgreSQL dumps used in the DSN 2026 evaluation: A smaller attack-only dataset for false-negative evaluation, containing real-world reentrancy exploit transactions from 73 attacks (1,122 exploit transactions in total). A full evaluation dataset for false-positive evaluation, containing 1,077,298 non-trivial randomly sampled transactions. The first dataset is a subset of the second and is provided separately to support validators with limited time, storage, or hardware; validators with sufficient resources may download and restore only the full dataset and run both false-negative and false-positive evaluations from it. The data are preprocessed and cached to support reproducible experiments without external API access, enabling validators and researchers to reproduce ReSect’s accuracy and large-scale false-positive evaluation. For detailed instructions, please see README.md.