Datasets:

quailrobot
/

netflow-v1-sample

license: cc-by-nc-sa-4.0
task_categories:
  - tabular-classification
tags:
  - intrusion-detection
  - cybersecurity
  - network-flows
  - synthetic
  - tabular
  - anomaly-detection
pretty_name: QM Synthetic Network Intrusion Flows
configs:
  - config_name: flows
    data_files: flows_sample.csv
    default: true
  - config_name: incidents
    data_files: incidents.csv

QM Synthetic Network Intrusion Flows - Free Sample

Buy the full commercial edition: $5 USD -> Polar checkout, instant download
This free sample is non-commercial (CC BY-NC-SA 4.0). The paid full edition has a commercial licence.

Summary

Synthetic enterprise network flow records with 7 labelled attack types, for intrusion-detection / SOC models; the paid full edition can be used commercially.

Best for: IDS / SOC model prototyping, feature engineering for per-host aggregates, detection-rule testing, teaching
Not for: claiming real-world detection rates or certifying a security product

Quick start

from datasets import load_dataset
ds = load_dataset("quailrobot/netflow-v1-sample", split="train")  # main table: flows_sample.csv
# pandas alternative: pd.read_csv("hf://datasets/quailrobot/netflow-v1-sample/flows_sample.csv")

Facts

Task: tabular binary + multi-class classification (intrusion detection), anomaly detection, alert triage
Labels: label (0/1); attack_type = port_scan, ssh_brute_force, ddos, c2_beaconing, data_exfiltration, lateral_movement, dns_tunneling; campaign_id; incidents.csv (type, low_and_slow, start)
Full edition size: 4,291,839 flows, 1,500 hosts, 28 days, 168 attack campaigns, attack rate 0.0211 (zip 65 MB)
Free sample size: 562,530 flows = first 3 days, all 7 attack types (flows_sample.csv) + the campaigns that start in that window
Format: full: Parquet (flows) + CSV (incidents); sample: CSV
What's included (full edition): flows.parquet, incidents.csv, stats.json, benchmark.json, bench_netflow.py, README.md, LICENSE.txt
Price: $5 USD; checkout may display the equivalent in your local currency
Buy URL (primary): https://buy.polar.sh/polar_cl_GGObtkVsr8IkPlgEdD2gD4M1kfp33AE84Jlr9360OY0
Licence (full edition): LicenseRef-QuailModel-Commercial (commercial use allowed, no resale of the data)
Licence (free sample): CC-BY-NC-SA-4.0
Validation: Our own test on the full edition (time split, last 11 days): gradient boosting on single-flow features ROC-AUC 0.937 / PR-AUC 0.260 (single flows are not enough); with 1-hour per-host aggregates 0.997 / 0.963; hard classes lateral_movement 0.020, data_exfiltration 0.456, ssh_brute_force 0.602 PR-AUC (benchmark.json + script included).
Data source: 100% synthetic, generated by QuailModel with AI assistance (generator code written with an AI model)
Catalog (all QuailModel datasets, catalog.json, llms.txt): https://quailrobot-quailmodel.static.hf.space
Last updated: 2026-10-10

Validation

Our own test on the full edition (time split, last 11 days): gradient boosting on single-flow features ROC-AUC 0.937 / PR-AUC 0.260 (single flows are not enough); with 1-hour per-host aggregates 0.997 / 0.963; hard classes lateral_movement 0.020, data_exfiltration 0.456, ssh_brute_force 0.602 PR-AUC (benchmark.json + script included).

Price & licence

Full edition: $5 USD. One-time payment, instant download after checkout: https://buy.polar.sh/polar_cl_GGObtkVsr8IkPlgEdD2gD4M1kfp33AE84Jlr9360OY0
QuailModel Commercial Dataset Licence (SPDX: LicenseRef-QuailModel-Commercial): you may train, evaluate and ship models, including in commercial products. You may not resell or redistribute the dataset itself.
Free sample (this page): CC BY-NC-SA 4.0 - free for non-commercial use.

Limitations

100% synthetic: not validated against real network captures.
Flow records only - no packet payloads.
External IPs come only from RFC 5737 documentation ranges.
label, attack_type and campaign_id are labels - exclude them from model inputs.

Custom dataset of YOUR object ($249)

Need data of YOUR object? Custom Object-Detection Dataset of Your Object (2,000 images), $249 USD -> order on Polar

Note: this is an image / object-detection service (not tabular data).
What you get: 2,000 labelled photoreal synthetic images (640x640 JPEG) of your own object or scenario (product, part, tool, drone, package, defect...), up to 3 classes, YOLO bounding boxes + data.yaml, train/val/test split, quality report
Licence: commercial use allowed
Price: $249 USD one-time; one round of adjustments included
Delivery: typically 3-5 business days after we receive your reference photos + rough dimensions
Optional sim-to-real test: send ~200 of your own labelled real images and we report how much the synthetic data improves a detector on them
Refund: full refund if we cannot deliver your request (14-day refund policy)
Limits: only objects you own or are allowed to use; no weapons or anything meant to harm people; no copied third-party 3D assets
Order URL: https://buy.polar.sh/polar_cl_AQu6LzRtqiQmKPlgPt0zePBtvWjJI4vULeFMQ4NLHH9
Details + contact: https://quailrobot-quailmodel.static.hf.space

This free sample: 562,530 flows = first 3 days, all 7 attack types (flows_sample.csv) + the campaigns that start in that window. Full commercial edition: 4,291,839 flows, 1,500 hosts, 28 days, 168 attack campaigns, attack rate 0.0211 (zip 65 MB). Fully synthetic data; summary, facts, validation and limitations are in the block above.

Files

flows (Parquet in the full edition, CSV in the sample), incidents.csv; the full edition adds stats.json, benchmark.json and bench_netflow.py.

How it was made

Produced by QuailModel's own simulator, including legitimate activity alongside the labelled patterns. Labels are exact, because they are known by construction.

Credits

No third-party data was used.

Licence

Sample edition: CC BY-NC-SA 4.0 (non-commercial). The full commercial edition is sold by QuailModel (see the buy link).

Disclosure

Generated by QuailModel with AI assistance (generator code written with an AI model); all data is synthetic / computer-generated. Validate on your own real data before production use.