As of tonight, a new version of the manuscript “On the well-posedness of Bayesian inverse problems” is available in the arXiv. Aside from a slight change of the paper’s focus, I have added some new results concerning stability in the Wasserstein distance and considered the case of infinite-dimensional data spaces with additive Gaussian noise. The latter complements the results we have already had for finite-dimensional noise – here, we could already show well-posedness independently of prior and forward model. Additionally, the infinite-dimensional case gives a new connection between this manuscript and the recent article of Christian Kahle, Kei Fong Lam, Elisabeth Ullmann, and me; see (2019, SIAM/ASA J. Uncertain. Quantif. 7(2), p. 526-552).