Vulnerable Verified Smart Contracts

<b>Artifact Description</b>Vulnerable Verified Smart Contracts is a dataset of real vulnerable Ethereum smart contracts. Based on the manually labeled Benchmark dataset of Solidity smart contracts. A total of 609 vulnerable contracts are provided, containing 1,117 vulnerabilities.The dataset is split into: "train", "validation" and "test". Each file is in the Apache Parquet data file format.<b>Environment Setup</b>The Pandas library for Python is required to load the dataset. Both Unix-based and Windows systems are supported.<b>Getting Started</b>The following code snippet demonstrates how to load the dataset into a Pandas DataFrame.<br><br>&gt;&gt;&gt; import pandas as pd<br>&gt;&gt;&gt; df = pd.read_parquet("path/to/data")<b>License</b>All Smart Contracts in the dataset are subject to their own original licenses.

<b>数据集说明</b>带漏洞的经校验智能合约（Vulnerable Verified Smart Contracts）数据集收录了真实存在漏洞的以太坊（Ethereum）智能合约。本数据集基于经人工标注的Solidity（Solidity）智能合约基准数据集构建，共包含609个存在漏洞的智能合约，涵盖1117个安全漏洞。数据集划分为训练集（train）、验证集（validation）与测试集（test），所有数据文件均采用Apache Parquet（Apache Parquet）格式存储。<b>环境配置</b>加载该数据集需依赖Python的Pandas（Pandas）库，同时支持基于Unix的操作系统与Windows系统。<b>快速上手</b>以下代码示例演示了如何将数据集加载至Pandas（Pandas） DataFrame（DataFrame）中：
>>> import pandas as pd
>>> df = pd.read_parquet("path/to/data")<b>许可协议</b>数据集中所有智能合约均遵循其各自的原始许可协议。