Hotspots, or mutations that recur at the same genomic site across multiple tumors, have been conventionally interpreted as strong universal evidence of somatic positive selection, unequivocally pinpointing genes driving tumorigenesis. Here, we demonstrate that this convention is falsely premised on an inaccurate statistical model of background mutagenesis. Many hotspots are in fact passenger events, recurring at sites that are simply inherently more mutable rather than under positive selection, which current background models do not account for. We thus detail a log-normal-Poisson (LNP) background model that accounts for variation in site-specific mutability in a manner consistent with models of mutagenesis, use this model to show that the tendency to generate passenger hotspots pervades all common mutational processes, and apply it to a ⇠10, 000 patient cohort from The Cancer Genome Atlas to nominate driver hotspots with far fewer false positives compared to conventional methods. As the biomedical community faces critical decisions in prioritizing putative driver mutations for deep experimental characterization to assess therapeutic potential, we offer our findings as a guide to avoid wasting valuable scientific resources on passenger hotspots. Identification of significantly mutated regions across cancer types highlights a rich landscape of functional molecular alterations. Nat. Genet., 48 (2):117-125, February 2016. Hanadi Baeissa, Graeme Benstead-Hume, Christopher J Richardson, and Frances M G Pearl. Identification and analysis of mutational hotspots in oncogenes and tumour suppressors. Oncotarget, 8(13):21290-21304, 2017. F Bahram, N von der Lehr, C Cetinkaya, and L G Larsson. c-myc hot spot mutations in lymphomas result in inefficient ubiquitination and decreased proteasomemediated turnover. Blood, 95(6):