In this paper, we uncover the Bloom paradox in Bloom Filters: Sometimes, the Bloom Filter is harmful and should not be queried. We first analyze conditions under which the Bloom paradox occurs in a Bloom Filter and demonstrate that it depends on the a priori probability that a given element belongs to the represented set. We show that the Bloom paradox also applies to Counting Bloom Filters (CBFs) and depends on the product of the hashed counters of each element. In addition, we further suggest improved architectures that deal with the Bloom paradox in Bloom Filters, CBFs, and their variants. We further present an application of the presented theory in cache sharing among Web proxies. Lastly, using simulations, we verify our theoretical results and show that our improved schemes can lead to a large improvement in the performance of Bloom Filters and CBFs.