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:

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 = {Available at: https://huggingface.co/datasets/DeepInstinct/DeepURLBench} }