README.md

# DeepURLBench

**DeepURLBench** is a large-scale benchmark dataset for real-world URL classification, developed by Deep Instinct's research team.

## Dataset Overview

The dataset includes two subsets in Parquet format:

### 🟢 `urls_with_dns`

Contains additional DNS resolution data:

- `url`: The URL being analyzed.
- `first_seen`: The timestamp when the URL was first observed.
- `TTL` (Time to Live): DNS TTL value.
- `label`: The classification label (`malware`, `phishing`, or `benign`).
- `ip_address`: List of resolved IP addresses.

### 🔵 `urls_without_dns`

Contains only the core metadata:

- `url`: The URL being analyzed.
- `first_seen`: The timestamp when the URL was first observed.
- `label`: The classification label (`malware`, `phishing`, or `benign`).

## How to Load

You can load the dataset using the Hugging Face `datasets` library:

```python
from datasets import load_dataset

# Load the subset with DNS data
ds_dns = load_dataset("DeepInstinct/DeepURLBench", "with_dns")

# Load the subset without DNS data
ds_no_dns = load_dataset("DeepInstinct/DeepURLBench", "without_dns")
'''

## License

This dataset is available under the CC BY-NC 4.0 License.
## Citation

@misc{deepurlbench2025,
  author       = {Deep Instinct Research Team},
  title        = {DeepURLBench: A large-scale benchmark for URL classification},
  year         = {2025},
  howpublished = {\\url{https://huggingface.co/datasets/DeepInstinct/DeepURLBench}}
}