Zia Penetration Testing: 20 Million Synthetic Web Application Security Records

20,000,000 rows of synthetic penetration testing findings generated by Zia Data Labs. The dataset simulates a full enterprise vulnerability management pipeline at production scale, focusing on web application security. It was last updated on the platform in June 2026.

Use Cases

• Training ML models for automated vulnerability detection based on synthetic penetration testing findings.
• Benchmarking security analysis tools against a large-scale, simulated enterprise vulnerability pipeline.
• Researching attack patterns and security weaknesses in web applications based on OWASP-related data.
• Developing and testing data pipelines for security information and event management (SIEM) systems using high-fidelity synthetic logs.

Strengths

• Contains 20,000,000 rows, providing a massive scale for model training and simulation.
• Simulates a full enterprise vulnerability management pipeline, suggesting comprehensive coverage of security findings.
• Data is stored in a single Parquet file of approximately 2.5 GB, which is efficient for storage and processing.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality and feature details require manual inspection after download.
• The synthetic nature of the data may not perfectly reflect real-world attack vectors and distributions.

Provenance

Source

Zia Data Labs

Collection Method

Synthetically generated for machine learning and cybersecurity research.

Freshness

Last updated 2026-06-10 12:08:49; freshness should be verified.