Cybersecurity Threat Dataset with 5,000 Labeled Malware Records

Cybersecurity Threat Dataset for Malware Detection contains 5,000 labeled cyber threat intelligence records. The records include Indicators of Compromise (IOCs) intended for machine learning applications. The author, organization, and last update date are unknown.

Use Cases

• Train malware classification models based on labeled threat intelligence records.
• Develop IOC (Indicators of Compromise) matching and correlation systems based on the provided IOCs.
• Benchmark machine learning algorithms for cybersecurity applications based on the labeled dataset.

Strengths

• Dataset contains 5,000 labeled records, providing a substantial base for model training.
• Data includes Indicators of Compromise (IOCs), a key feature for cybersecurity analysis.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is known, but the total number of features per record is unknown.
• Last update date is unknown; freshness unverified.

Provenance

Collection Method

Likely gathered from threat intelligence feeds or security logs, but the specific method is unknown.