Spatial anonymization is an important step in the research workflow for many researchers. In this paper we present BlockR, an open-source tool in R for areal spatial anonymization and visualization. After using a shape-clustering algorithm (SKATER), the underlying tool performs a series of affine transformations on the region of interest followed by “blockification” and border obfuscation processes to obscure the underlying shape. Importantly, BlockR anonymizes areal units while preserving contextually important spatial characteristics and administrative properties. Measures of disclosure risk are provided through a theoretical analysis of Hausdorff distances and the use of a neural network image classifier.