The global demand for key metals (Ni, Cu, and Co), coupled with the depletion of easily discoverable resources, necessitates advanced exploration methodologies for volcanogenic massive sulphide (VMS) deposits. Gossans, key surface indicators of VMS and associated gold mineralization, are particularly challenging to identify in regions with complex geological settings, deep weathering, and rugged topography, such as the Ariab mining district of the Arabian Nubian Shield (ANS). This study investigated the novel application of the space borne hyperspectral PRISMA (PRecursore IperSpettrale della Missione Applicativa) sensor, leveraging its high spectral resolution for gossan detection. An integrated approach was employed, incorporating color composites, band ratios, density slicing, and a hyperparameter-optimized Random Forest classifier. The model achieved an overall accuracy exceeding 80 %, demonstrating its efficacy for scalable gossan mapping. The results were validated through spectral analysis, confirming diagnostic jarosite signatures and extensive fieldwork. This research establishes PRISMA as a powerful, exploration-ready tool for early-stage targeting of auriferous VMS deposits in the ANS and similar arid shield terrains globally.