metadata
license: cc-by-4.0
task_categories:
- text-classification
- token-classification
language:
- en
pretty_name: SmartUecDB
size_categories:
- 1K<n<10K
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:
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)
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:
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:
@misc{smartuecdb25,
author = {B. William},
title = {SmartUecDB},
year = {2026},
publisher = {Hugging Face},
url= {https://huggingface.co/datasets/Adson59/SmartUecDB},
}