ZiaSyntheticDataPenetrationTesting: 20 Million Synthetic Web App Security Findings

Zia Data Labs generated a production-grade synthetic dataset containing 20,000,000 rows of high-fidelity web application penetration testing findings. The dataset simulates a full enterprise vulnerability management pipeline at production scale and is stored in a single Parquet file of approximately 2.5 GB. It was last updated on June 7, 2026.

Use Cases

• Training ML models for automated vulnerability detection based on synthetic penetration testing findings.
• Benchmarking security analytics tools against a large-scale, simulated enterprise vulnerability pipeline.
• Developing and testing anomaly detection algorithms for web application security incidents.
• Simulating security operations center (SOC) workflows and data flows for research and development.

Strengths

• Contains 20,000,000 rows, providing a large-scale data resource.
• Stored in a single, efficient Parquet file of approximately 2.5 GB.
• Designed to simulate a full enterprise vulnerability management pipeline at production scale.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Data is synthetic, which may limit its direct applicability to real-world threat models and distributions.

Provenance

Source

Zia Data Labs

Collection Method

Synthetically generated.

Freshness

Last updated 2026-06-07 18:59:38; freshness should be verified.