Datasetpublic

Adson59/SmartUecDB

SmartUecDB Description SmartUecDB is a specialized, multimodal dataset designed for the high-fidelity detection of vulnerabilities in smart contract bytecode, with a primary focus on identifying unchecked external calls. The dataset curates a robust corpus of EVM-compatible execution traces and structural graph representations, enabling the training of Graph Neural Networks (GNN) to pinpoint insecure dispatch patterns and reentrancy vectors. Usage… See the full description on the dataset page: https://huggingface.co/datasets/Adson59/SmartUecDB.

sourceHugging Facecc-by-4.0updated 4mo agoView on Hugging Face

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SmartUecDB

Description

SmartUecDB is a specialized, multimodal dataset designed for the high-fidelity detection of vulnerabilities in smart contract bytecode, with a primary focus on identifying unchecked external calls. The dataset curates a robust corpus of EVM-compatible execution traces and structural graph representations, enabling the training of Graph Neural Networks (GNN) to pinpoint insecure dispatch patterns and reentrancy vectors.

Usage

You can start by downloading the primary dataset folder:

python

import os
import requests
import tarfile
import shutil

FILE = "data.tar"
url = f"https://huggingface.co/datasets/Adson59/SmartUecDB/resolve/main/{FILE}"

def download_dataset(url, filename):
    response = requests.get(url)
    if response.status_code == 200:
        with open(filename, 'wb') as f:
            f.write(response.content)
        print(f"Successfully downloaded {filename}")
    else:
        print(f"Failed to download. Status code: {response.status_code}")

download_dataset(url, FILE)

python

with tarfile.open("data.tar", 'r') as tar:
    tar.extractall(".")

Structure

The following is the standard directory structure for the dataset, organized to support modular GNN training and inference pipelines:

bash

SmartUecDB/
├── processed/          # cleaned and prepared rows
├── raw/                # original rows collected from the smartmaldb
├── split/              # Train/validation/test splits defined for reproducible model benchmarking

Citation

If you use this dataset, cite:

bibtex

@misc{smartuecdb25,
  author = {B. William},
  title = {SmartUecDB},
  year = {2026},
  publisher = {Hugging Face},
  url= {https://huggingface.co/datasets/Adson59/SmartUecDB},
}

license: cc-by-4.0 ---