Brain diffusion MRI data may present unpredictable artifacts like those related to insufficient fat suppression. Given the quantity of data collected in state-of-the-art diffusion protocols, such artifacts are challenging to detect by visual inspection. In this study, we implemented and tested an automated method that helps to detect such artifacts, identifying the slice(s) where they are present. The method is based on the automated generation of the shape of the artifact from the skull at each slice and subsequent search of the pattern in the diffusion data. The method gave high specificity (0.977) and sensitivity (0.889).