AI-based malicious package detection focuses on identifying potentially harmful or deceptive third-party software packages before they are introduced into an application's dependency environment. It involves analyzing package source code, examining package metadata, extracting relevant code and naming characteristics, and identifying suspicious patterns that may indicate malicious functionality or attempts to impersonate legitimate packages. By combining transformer-based code analysis with machine learning-driven anomaly detection, this approach helps classify potentially malicious packages, identify unusual dependency characteristics, and flag suspicious components for further security review. The resulting assessment supports pre-installation risk evaluation, safer dependency selection, and the prevention of software supply-chain threats that could compromise application integrity or introduce unauthorized code execution.