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.
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This dataset consists of over 40K real world Ethereum smart contracts.
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Download this resource at Ethereum_smart_contract.
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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}
}
- 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.
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This dataset contains over 12K Ethereum smart contracts and concerns eight types of vulnerabilities.
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Check the pattern design for more details.
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Download this resource at Dataset.
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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}
}