Zia Malware Detection: 20 Million Synthetic Analysis Events

20,000,000 rows of high-fidelity synthetic malware analysis events designed for security AI training. The dataset is produced by Zia-Data-Labs and was last updated on June 12, 2026. It avoids exposing real binaries or proprietary threat intelligence.

Use Cases

• Train binary malware classifiers based on synthetic malware analysis events.
• Develop multi-class family attribution models based on behavioral features.
• Build behavioral anomaly detectors based on the high-fidelity event data.

Strengths

• Contains over 20,000,000 rows of data.
• Built specifically for production-grade training tasks.
• Uses synthetic data to avoid exposing real binaries or live telemetry.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Zia-Data-Labs

Collection Method

Synthetic data generation.

Freshness

Last updated 2026-06-12 04:51:52; freshness should be verified.