<p>Identifying counterfeit products poses substantial challenges for both businesses and consumers. Although the financial implications for companies can be significant, the potential risks to consumer safety are a major concern. The inflexible approach of conventional supply chain management techniques has limitations, as they rely heavily on centralized control and physical tracking. Blockchain technology provides a transparent and secure solution for detecting and combating fraudulent products by facilitating the verification of product authenticity through immutable records containing ‘tamper-proof’ data throughout the supply chain system. This paper reviews the literature in the area and provides a summary of the key ideas and toolset needed to develop a blockchain-based counterfeit detection system. Furthermore, we propose a system for detecting fake protein supplement goods using blockchain technology. Our approach enhances this system by integrating an AI-enabled fraud detection layer to improve the accuracy and efficiency of counterfeit detection. Unlike traditional blockchain solutions that emphasize merely traceability and immutability, our framework utilizes machine learning models, specifically XGBoost model, to analyze fraudulent transaction patterns, detect anomalies, and send real-time alerts. The results show that the framework has the potential to improve transparency and traceability in supply chains, increase the efficiency and accuracy of counterfeit detection systems, and alleviate the negative economic and social repercussions of counterfeit items.</p>