Datasets:
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.
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, orbenign).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, orbenign).
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} }