Abstract Automated search methods based on Satisfiability Modulo Theory (SMT) problems are being widely used to evaluate the security of block ciphers against distinguishing attacks. While these methods provide a systematic and generic methodology, most of their software implementations are limited to a small set of ciphers and attacks, and extending these implementations requires significant effort and expertise. In this work, the authors present cryptographic algorithms for distinguishing attacks ( CASCADA ), an open‐source Python library to evaluate the security of cryptographic primitives, specially block ciphers, against distinguishing attacks with bit‐vector SMT solvers. The tool CASCADA implements the bit‐vector property framework herein proposed and several SMT‐based automated search methods to evaluate the security of ciphers against differential, related‐key differential, rotational‐XOR, impossible‐differential, impossible‐rotational‐XOR, related‐key impossible‐differential, linear and zero‐correlation cryptanalysis. The library CASCADA is the result of a huge engineering effort, and it provides many functionalities, a modular design, an extensive documentation and a complete suite of tests.