CLAMPD-1905-Dataset

CLAMPD-1905 is the first comprehensive cross-language dataset for malicious package detection research, offering unified feature representations and full reproducibility across PyPI and npm ecosystems. This dataset enables standardized benchmarking of malware detection tools across diverse software supply chain ecosystems. Built on curated packages from MalwareBench, CLAMPD-1905 includes 23,764 balanced software packages (11,882 benign and 11,882 malicious) from PyPI and npm, each represented as a 1905-dimensional multimodal feature vector. These vectors combine static metadata (9 features), dependency graph embeddings (128 dimensions), and API behavioral features (1768 dimensions) extracted from over one million source files. This unified representation eliminates ecosystem-specific preprocessing requirements, facilitates reproducible experiments, and supports research on cross-ecosystem supply chain security threats. Key Features: Cross-Ecosystem Coverage: Unified feature space spanning PyPI and npm Multimodal Feature Integration: Metadata, HAN dependency graph embeddings, and BERT API usage features Perfect Class Balance: 23,764 packages (11,882 benign, 11,882 malicious) Advanced Feature Engineering: Pre-computed 1905-dimensional feature vectors for direct model training Research Ready: Standardized format for ML model evaluation and reproducibility Comprehensive Representation: Captures structural, semantic, and behavioral characteristics