---
gated: true
license: other
license_name: proprietary-commercial
language:
  - en
tags:
  - cybersecurity
  - synthetic
  - incident-response
  - siem
  - soc
  - threat-detection
task_categories:
  - tabular-classification
  - tabular-regression
  - text-classification
size_categories:
  - 10M<n<100M
extra_gated_heading: Access Verification Required
extra_gated_description: >-
  To access this 20M row dataset, you must first complete the $20.00 access fee
  via PayPal and provide your payment details below.
extra_gated_button_content: Request Access
extra_gated_fields:
  PayPal Transaction ID or Payer Email: text
---

# Zia Incident Response — 20M Synthetic Records

## Dataset Description

A production-grade dataset containing over 20,000,000 rows of high-fidelity enterprise incident response logs. Built specifically for training ML-driven triage and response models, stress-testing SIEM/SOC pipelines, and benchmarking incident lifecycle workflows — without exposing real credentials or PII.

- **Massive Scale:** 20M+ rows delivered in Parquet format
- **Rich Schema:** 17 core columns covering the full incident lifecycle from detection to resolution
- **Realistic Distribution:** Spans 12 incident categories with true-to-life severity weighting
- **Incident Lifecycle Coverage:** From initial alert trigger through containment, eradication, and closure

## ⚠️ SAFETY & FIDELITY NOTICE — Zia-Data-Labs

This dataset is high-fidelity synthetic data engineered to mirror real-world patterns with exceptional accuracy. In benchmark testing, leading AI models treat this data as authentic — recognizing edge cases, flagging anomalies, and generating functional code with zero scrubbing required.

Because of this realism, improper use during model fine-tuning can trigger deep behavioral shifts in production systems.

**This dataset is strictly intended for research, evaluation, and development within isolated sandbox or staging environments.**

Zia-Data-Labs provides all datasets on an "as-is" basis. We do not assume liability for downstream model behavior, deployment risks, or production system impacts. Users are solely responsible for conducting independent safety audits prior to any live deployment.

---

## Instant Free Sample

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

[Download 50-Row Free Sample (CSV)](https://huggingface.co/datasets/Zia-Data-Labs/ZiaSyntheticDataSecurityIncidentResponse/resolve/main/sample_50rows.csv)

## Try the AI Challenge

Paste this free sample into Gemini or ChatGPT. Ask the AI to run a full incident response analysis. Both models independently flag the embedded anomalies, isolate the highest-risk incident IDs, and write functional Python code to graph severity trends. Independently scored 100/100 for realism — no scrubbing necessary.

## Access & Pricing

### 1. Full Dataset Access — $20.00

All 20,000,000 rows on Hugging Face.

- Pay securely via PayPal: [Click Here to Pay](https://www.paypal.com/ncp/payment/TRY8ADZTN2ETN)
- 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.

## How to Load

\`\`\`python
from datasets import load_dataset

ds = load_dataset("ziadatalabs/Zia-Synthetic-Data_Security-Incident-Response")
print(ds['train'][0])
\`\`\`

## Data Schema & Fields

| Field Name | Data Type | Description |
|------------|-----------|-------------|
| Incident_ID | string | Unique incident tracking identifier |
| Timestamp_Detected | string | Date and time the incident was captured |
| Incident_Type | string | Category of attack (Ransomware, Phishing, etc.) |
| Severity | string | Critical, High, Medium, Low |
| Affected_System | string | Corporate asset targeted |
| Region | string | Geographic location of targeted infrastructure |
| Responding_Team | string | Internal security cell handling mitigation |
| MTTD_Hours | float32 | Mean Time to Detect (fractional hours) |
| MTTR_Hours | float32 | Mean Time to Respond (fractional hours) |
| Contained | string | Whether threat was successfully isolated |
| Compliance_Check | string | Post-incident evaluation status |
| Playbook_Followed | string | Whether SOPs were adhered to |
| Status | string | Final lifecycle state of the ticket |
| False_Positive | string | Whether the alert was a benign event |
| Escalated_To_CISO | string | Executive leadership visibility required |
| IR_Score | float32 | Incident response performance score (81-100) |
| WM_TAG | string | Synthetic generation watermarking tag |

## Technical Specifications

- **Format:** Apache Parquet
- **Total Records:** 20,000,000 rows
- **License:** Proprietary / Custom Commercial
- **Producer:** Zia Data Labs (2026)
- **Strictly Prohibited:** Public redistribution, resale, or mirroring of the raw Parquet files is forbidden under our commercial terms.

## Citation

Zia Data Labs, 2026.
https://huggingface.co/datasets/ziadatalabs/Zia-Synthetic-Data_Security-Incident-Response