<b>MH-1M Dataset</b>

The rapid and widespread increase of Android malware presents substantial obstacles to cybersecurity research. In order to revolutionize the field of malware research, we present the MH-1M dataset, which is a thorough compilation of <b>1,340,515 APK</b> samples. This dataset encompasses a wide range of diverse attributes and metadata, offering a comprehensive perspective. The utilization of the VirusTotal API guarantees precise assessment of threats by amalgamating various detection techniques. Our research indicates that MH-1M is a highly current dataset that provides valuable insights into the changing nature of malware.MH-1M consists of 23,247 features that cover a wide range of application behavior, from intents::accept to apicalls::landroid/window/splashscreenview.remove. The features are categorized into four primary classifications:Feature TypesValuesAPICalls22,394Intents407OPCodes232Permissions214The dataset is stored efficiently, utilizing a memory capacity of <b>29.0 GB</b>, which showcases its substantial yet controllable magnitude. The dataset consists of <b>1,221,421 benign</b> applications and <b>119,094 malware</b> applications, ensuring a balanced representation for accurate malware detection and analysis.The MH-1M repository also offers a wide variety of metadata from APKs, providing useful data into the development of malicious software over a period of more than ten years. The Android features include a wide variety of metadata, which includes SHA256 hashes, file names, package names, compilation APIs, and various other details. This GitHub repository contains over 400GB of valuable data, making it the largest and most comprehensive dataset available for advancing research and development in Android malware detection.安卓恶意软件的快速蔓延与广泛传播给网络安全研究带来了严峻挑战。为推动恶意软件研究领域的革新，我们推出了MH-1M数据集，该数据集完整收录了**1,340,515个APK（Android Package Kit）样本**。本数据集涵盖丰富多样的属性与元数据，可提供全面的研究视角。通过整合多种检测技术，借助VirusTotal API可实现精准的威胁评估。本研究证实，MH-1M是时效性极强的数据集，可为恶意软件的演化特性提供极具价值的研究洞察。 MH-1M包含23,247项特征，覆盖应用的各类行为范畴，从`intents::accept`至`apicalls::landroid/window/splashscreenview.remove`。上述特征被划分为四大主要类别：API调用（APICalls）共22,394项，意图（Intents）共407项，操作码（OPCodes）共232项，权限（Permissions）共214项。 该数据集采用高效存储方案，总存储空间达**29.0 GB**，可见其规模庞大却易于管控。数据集包含**1,221,421个良性应用**与**119,094个恶意应用**，可实现均衡的样本分布，为精准的恶意软件检测与分析提供有力支撑。 MH-1M仓库还提供了海量APK相关元数据，可助力研究者洞悉十余年间恶意软件的演化轨迹。安卓相关特征涵盖丰富的元数据信息，包括SHA256哈希值、文件名、包名、编译API及其他各类细节。本GitHub仓库包含超过400GB的宝贵数据，是目前用于推进安卓恶意软件检测领域研究与开发的规模最大、内容最全面的公开数据集。