Cybersecurity threats are increasingly exploiting vulnerabilities in human perception. This makes it necessary to develop advanced frameworks that deal with both technical and human factors in vulnerability analysis. This article reviews the current state of the art in cognitive vulnerability analysis. It focuses on a predictive and proactive approach supported by machine learning techniques. Survey of selected cohort models and behavioral safety assessments. We propose an approach for building an intelligent, predictive, and proactive cognitive vulnerability framework. Our review highlights important gaps in existing research. This is especially true of the challenge of integrating human behavior into cybersecurity models and ethical considerations related to the use of behavioral data.