| Messi-Q/AMEVulDetector |
49 |
|
0 |
0 |
about 3 years ago |
0 |
|
3 |
|
Python |
| Smart Contract Vulnerability Detection From Pure Neural Network to Interpretable Graph Feature and Expert Pattern Fusion (IJCAI-21 Accepted) |
| MANDO-Project/ge-sc |
19 |
|
0 |
0 |
over 2 years ago |
0 |
|
1 |
mit |
Solidity |
| MANDO is a new heterogeneous graph representation to learn the heterogeneous contract graphs' structures to accurately detect vulnerabilities in smart contract source code at both coarse-grained contract-level and fine-grained line-level. |
| bhaumik-choksi/Loan |
10 |
|
0 |
0 |
over 7 years ago |
0 |
|
0 |
|
Python |
| Smart P2P lending using Ethereum smart contracts and deep learning |
| zulhfreelancer/truffle-events |
7 |
|
2 |
3 |
over 3 years ago |
7 |
July 10, 2018 |
3 |
mit |
JavaScript |
| A simple utility library to form a transaction for deep event testing |
| MANDO-Project/ge-sc-transformer |
7 |
|
0 |
0 |
over 2 years ago |
0 |
|
1 |
mit |
Solidity |
| MANDO-HGT is a framework for detecting smart contract vulnerabilities. Given either in source code or bytecode forms, MANDO-HGT adapts heterogeneous graph transformers with customized meta relations for graph nodes and edges to learn their embeddings and train classifiers for detecting various vulnerability types in the contracts' nodes and graphs. |
| Messi-Q/ReChecker |
6 |
|
0 |
0 |
almost 5 years ago |
0 |
|
0 |
mit |
Python |
| ReChecker: Towards Automated Reentrancy Detection for Smart Contracts Based on Sequential Models |
| MANDO-Project/ge-sc-machine |
5 |
|
0 |
0 |
about 3 years ago |
0 |
|
0 |
mit |
Python |
| MANDO-GURU, a deep graph learning-based tool, aims to accurately detect vulnerabilities in smart contract source code at both coarse-grained contract-level and fine-grained line-level. |
