Escalated groundwater contamination around the world developed the idea of aquifer vulnerability, which has widely been employed globally to safeguard groundwater from contamination. Several extensive studies have been done to evaluate the degree of groundwater vulnerability using various techniques. However, a comprehensive assessment of existing literature in order to identify major research gaps associated with aquifer vulnerability is still required. The current study provides a critical overview of several groundwater risk assessment methodologies, including the GIS-based DRASTIC and modified DRASTIC methods, application of Artificial Intelligence (AI) and Machine Learning techniques, and integrated approach for both intrinsic and specific vulnerability assessment. The study discusses validation of DRASTIC model and its comparison with a few other methodologies as well. The paper also highlights the international approach (time dimension in groundwater vulnerability, integrated process based and isotopic studies, etc.) that needs to be practiced rigorously on a larger scale in India. A descriptive summary of the literature indicates that a multidisciplinary and integrated framework such as understanding contaminant type, uncertainties in vadose zone need to be implemented in a much more comprehensive way, especially in India. A conceptual framework that is both reasonably adaptable and scientifically sound must be created for specific vulnerability assessment.