Recommender systems are an effective solution for addressing the problem of information overload. They are extensively used to deliver personalized content and services to users accurately. A plethora of recommender systems have been developed for various domains which requires the analysis of huge number of users’ personal liking and opinions. Most of the recommender models focus on the recommendation preciseness and accuracy thus ignoring security and privacy of the users’ sensitive data. Different techniques have been used to tackle this issue, but none of the algorithms proves to be effective. To improve recommender system security and privacy, blockchain technology seems to have the potential. This is owing to its security, privacy, and trust-building abilities. This study presents an overview of recommender system based on blockchain with its characteristics and benefits in various domains. It also discusses the challenges and open issues which are to be considered while working in this domain. The results not only make a valuable contribution to the progress of secure recommender systems but also provide opportunities for the incorporation of blockchain technology in other personalized recommendation fields.