Datasets:

DeepInstinct
/

DeepURLBench

license: cc-by-nc-4.0
task_categories:
  - text-classification
language:
  - en
tags:
  - cybersecurity
pretty_name: DeepURLBench
size_categories:
  - 10M<n<100M

DeepURLBench

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

⚠️ Warning and Usage Disclaimer

This dataset contains real-world URLs labeled as malware, phishing, or benign, including domains that were associated with harmful or fraudulent activity at the time of collection. Do not attempt to visit or interact with any of the URLs in this dataset.

This dataset is intended solely for research and educational purposes in cybersecurity and machine learning. We strongly recommend using it in a read-only context, and not resolving or querying any of the included domains or IP addresses.

Deep Instinct assumes no responsibility for misuse of the dataset.

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).

Important Notes on Splitting

Although Hugging Face shows each loaded file under the "train" split by default, this dataset does not include predefined train/validation/test splits.

Instead, the intended splitting strategy is described in detail in our paper. In brief, we recommend splitting the data chronologically by the first_seen field, so that evaluation is performed on newer, unseen URLs — simulating real-world deployment.

Each subset (urls_with_dns and urls_without_dns) is designed to be loaded independently, as shown below.

How to Load

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

from datasets import load_dataset

ds_with_dns = load_dataset(
    "DeepInstinct/DeepURLBench",
    data_files="urls_with_dns.parquet"
)

ds_without_dns = load_dataset(
    "DeepInstinct/DeepURLBench",
    data_files="urls_without_dns.parquet"
)

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} }