Pinned Repositories
.github
ge-sc
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.
ge-sc-bytecode
The resource applied Graph Learning on smart contract vulnerability detection in bytecode form.
ge-sc-llm
Heterogeneous Graph Transformers with Large Language Models for Smart Contract Vulnerability Detection
ge-sc-machine
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.
ge-sc-transformer
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.
original-ge-sc
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.
MANDO's Repositories
MANDO-Project/ge-sc
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.
MANDO-Project/ge-sc-machine
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.
MANDO-Project/ge-sc-transformer
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.
MANDO-Project/ge-sc-bytecode
The resource applied Graph Learning on smart contract vulnerability detection in bytecode form.
MANDO-Project/ge-sc-llm
Heterogeneous Graph Transformers with Large Language Models for Smart Contract Vulnerability Detection
MANDO-Project/.github
MANDO-Project/original-ge-sc
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.