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MH-1M: A 1.34 Million-Sample Multi-Feature Android Malware Dataset with Rich Metadata.

Hendrio Bragança¹, Diego Kreutz², Vanderson Rocha³

¹Federal University of Amazonas (UFAM), Institute of Computing, Manaus-AM, 69.077-000, Brazil. hendrio.luis@icomp.ufam.edu.br.

Scientific Data

|December 31, 2025

Summary

This summary is machine-generated.

This study introduces MH-1M, a large Android malware dataset for advanced research. It aids in understanding evolving malware threats through comprehensive data and analysis.

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Area of Science:

Computer Science
Cybersecurity
Data Science

Background:

Android malware poses a significant and evolving threat to mobile security.
Existing datasets may lack the scale or detail required for advanced malware analysis.

Purpose of the Study:

To introduce MH-1M, a comprehensive dataset for Android malware research.
To facilitate advanced analysis of Android malware through open data access.

Main Methods:

Compiled a dataset of 1,340,515 Android applications.
Utilized the VirusTotal API with multiple detection engines for malware classification.
Extracted features and collected extensive metadata for each application.

Main Results:

The MH-1M dataset contains over 1.3 million Android applications.
The dataset includes comprehensive metadata and VirusTotal analysis results.
Over 400 GB of data is available across Figshare, Harvard Dataverse, and GitHub repositories.

Conclusions:

The MH-1M dataset is a valuable resource for studying the current landscape of Android malware.
Open access to this large-scale dataset will advance Android malware research and defense strategies.