Funded_nisl
FUNDED is a novel learning framework for building vulnerability detection models.
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Funded_nisl | 93 | 4 months ago | 1 | Python | ||||||
| FUNDED is a novel learning framework for building vulnerability detection models. | ||||||||||
| Ge Sc | 19 | 5 months ago | 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. | ||||||||||
| Dynamit | 17 | 5 months ago | mit | Jupyter Notebook | ||||||
| Dynamit: Dynamic Vulnerability Detection of Ethereum Smart Contracts Using Machine Learning by @mojtaba-eshghie | ||||||||||
| Pwnbert | 14 | a year ago | mit | Python | ||||||
| A project based on Fine-tuned BERT to detect GLIBC vulnerabilities. | ||||||||||
| Ge Sc Transformer | 7 | 6 months ago | 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. | ||||||||||
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Python
Machine Learning
Vulnerability Detection