A production-grade synthetic dataset containing 20,000,000 rows of high-fidelity threat intelligence telemetry. Generated by Zia Data Labs for machine learning engineers, SOC analysts, and cybersecurity researchers building next-generation threat detection and actor attribution models.

Massive Scale: 20M rows pre-sharded into Parquet files. Simulates continuous threat intelligence ingestion at enterprise production scale.
Rich Schema: 8 core columns covering the full threat intelligence lifecycle — from actor profiling and TTP mapping through to IOC tracking and severity scoring.
MITRE ATT&CK Aligned: Every row semantically bound to its correct MITRE tactic. TTPs strictly mapped to their accurate attack phases — no random tactic assignment.
Realistic Distribution: Actor Profiles / TTPs / IOCs / Campaigns — mirrors real-world enterprise threat intelligence pipeline ratios.
Cryptographic Integrity: SHA-256 per-row integrity hash computed over all fields for pipeline validation.

Instant Free Sample

Test the data quality immediately. No account or signup required.

Download 50-Row Free Sample (CSV)

Access & Pricing

1. Full Dataset Access — $20.00

All 20,000,000 rows on Hugging Face.

Pay securely via PayPal: Click Here to Pay
Email your Hugging Face username to: zia.data.team@protonmail.com
Your account will be whitelisted within 24 hours.

2. Custom 1 Billion Row Dataset — $499.99

Built to your exact specifications. Contact zia.data.team@protonmail.com for details.

Need enterprise-scale licensing (28B+ rows)? Contact zia.data.team@protonmail.com — custom quotes available with bulk pricing.

How to Load

from datasets import load_dataset

# Load the dataset using your Hugging Face Access Token
ds = load_dataset(
    "ziadatalabs/ZiaSyntheticDataThreatIntelligence",
    token="YOUR_HF_TOKEN"  # Found in your HF account settings under Access Tokens
)

# Print the first row
print(ds['train'][0])

Data Schema & Fields

Field Name	Data Type	Description
row_id	string	Unique record identifier (e.g., ZIA_TI_00000001)
timestamp	string	ISO-8601 UTC timestamp (YYYY-MM-DDTHH:MM:SSZ)
intel_category	string	Intelligence type: Actor Profile, TTP, IOC, or Campaign
indicator_value	string	The actual indicator — threat actor name, MITRE technique ID, IOC value, or campaign identifier
mitre_mapping	string	Semantically bound MITRE ATT&CK tactic (e.g., TA0001 - Initial Access)
actor_attribution	string	Attributed threat actor or group (e.g., LockBit, Lazarus, FIN7)
severity_score	int64	Risk score 0–100. Critical: 90–100. High: 70–89. Medium: 40–69. Low: 0–39
sha256_hash	string	Per-row SHA-256 integrity hash for pipeline validation

Technical Specifications

Property	Value
Format	Apache Parquet (Sharded)
Sample Format	CSV
Total Records	20,000,000 rows
Total Columns	8
License	Proprietary / Custom Commercial
Producer	Zia Data Labs (2026)

Strictly Prohibited: Public redistribution, resale, or mirroring of the raw Parquet shards is forbidden under our commercial terms.

Citation

Zia Data Labs, 2026. https://huggingface.co/datasets/ziadatalabs/ZiaSyntheticDataThreatIntelligence

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