Several mitigation strategies in form of warning messages against phishing attacks have continued to fail largely due to user negligence. Thus, it is important for researchers to focus not only on the accuracy of the provided recommendations but also on other factors that influence the acceptance of recommendations and the extent to which these recommendations are convincing or persuasive. In this paper, we present our ongoing approach that leverages on the Big 5 Personality trait model and users digital traces harvested from their social networks, thereafter, transformed into a personalized warning message. We argue that stimulating users through personal recommendations evokes an understanding of the implications of their actions or inaction.