/Smart-Contract-Dataset

Datasets for evaluating smart contract security analysis tools ( continuously updating... )

Smart Contract Dataset

This repository aims at releasing the smart contract datasets used in our works. Furthermore, we also present instructions on how to label a certain type of vulnerability and show the detailed pattern designs of investigated vulnerabilities.

Resource 1

  • This dataset consists of over 40K real world Ethereum smart contracts.

  • Download this resource at Ethereum_smart_contract.

  • Please cite one of our papers if you want to use this dataset in your paper:

@inproceedings{zhuangsmart,
  title={Smart Contract Vulnerability Detection using Graph Neural Network},
  author={Zhuang, Yuan and Liu, Zhenguang and Qian, Peng and Liu, Qi and Wang, Xiang and He, Qinming},
  booktitle={IJCAI},
  pages={3283--3290},
  year={2020}
}

@inproceedings{liu2021smart,
  title={Smart Contract Vulnerability Detection: From Pure Neural Network to Interpretable Graph Feature and Expert Pattern Fusion},
  author={Liu, Zhenguang and Qian, Peng and Wang, Xiang and Zhu, Lei and He, Qinming and Ji, Shouling},
   booktitle={IJCAI},
  pages={2751--2759},
  year={2021}
}

@article{liu2021combining,
  title={Combining Graph Neural Networks with Expert Knowledge for Smart Contract Vulnerability Detection},
  author={Liu, Zhenguang and Qian, Peng and Wang, Xiaoyang and Zhuang, Yuan and Qiu, Lin and Wang, Xun},
  journal={IEEE Transactions on Knowledge and Data Engineering},
  year={2021},
  publisher={IEEE}
}

Resource 2

  • This dataset concerns four types of vulnerabilities (i.e., reentrancy, timestamp dependency, integer overflow, dangerous delegatecall), where we give the preprocessing method.
  • Check instructions for how to label these vulnerabilities.
  • Download this resource at Dataset_preprocessing.

Resource 3

  • This dataset contains over 12K Ethereum smart contracts and concerns eight types of vulnerabilities.

  • Check the pattern design for more details.

  • Download this resource at Dataset.

  • Please cite our paper if you want to use this dataset in your paper:

@article{liu2023rethinking,
  title={Rethinking Smart Contract Fuzzing: Fuzzing With Invocation Ordering and Important Branch Revisiting},
  author={Liu, Zhenguang and Qian, Peng and Yang, Jiaxu and Liu, Lingfeng and Xu, Xiaojun and He, Qinming and Zhang, Xiaosong},
  journal={arXiv preprint arXiv:2301.03943},
  year={2023}
}