AI-based supply chain attack detection focuses on identifying vulnerable third-party dependencies and potentially malicious software packages that may introduce security threats into applications through external software components. It involves analyzing package metadata, dependency characteristics, known vulnerability information, and suspicious package indicators to distinguish potentially unsafe components from legitimate dependencies. By combining machine learning-based classification techniques with software package security analysis, this approach helps identify dependencies associated with known vulnerabilities, detect suspicious or malicious packages before installation, and prioritize components requiring further security investigation. The resulting findings support safer dependency selection, proactive supply chain threat detection, reduced exposure to compromised software components, and improved security throughout the software development and package management lifecycle.