Redis (Remote Dictionary Server) is a general purpose, in-memory database that supports a rich array of functionality, including various Probabilistic Data Structures (PDS), such as Bloom filters, Cuckoo filters, as well as cardinality and frequency estimators. These PDS typically perform well in the average case. However, given that Redis is intended to be used across a diverse array of applications, it is crucial to evaluate how these PDS perform under worst-case scenarios, i.e., when faced with adversarial inputs. We offer a comprehensive analysis to address this question. We begin by carefully documenting the different PDS implementations in Redis, explaining how they deviate from those PDS as described in the literature. Then we show that these deviations enable a total of 10 novel attacks that are more severe than the corresponding attacks for generic versions of the PDS. We highlight the critical role of Redis' decision to use non-cryptographic hash functions in the severity of these attacks. We conclude by discussing countermeasures to the attacks

End-to-end encrypted cloud storage offers a way for individuals and organisations to delegate their storage needs to a third-party, while keeping control of their data using cryptographic techniques. We conduct a cryptographic analysis of various products in the ecosystem, showing that many providers fail to provide an adequate level of security. In particular, we provide an in-depth analysis of five end-to-end encrypted cloud storage systems, namely Sync, pCloud, Icedrive, Seafile, and Tresorit, in the setting of a malicious server. These companies cumulatively have over 22 million users and are major providers in the field. We unveil severe cryptographic vulnerabilities in four of them. Our attacks invalidate the marketing claims made by the providers of these systems, showing that a malicious server can, in some cases, inject files in the encrypted storage of users, tamper with file data, and even gain direct access to the content of the files. Many of our attacks affect multiple providers in the same way, revealing common failure patterns in independent cryptographic designs. We conclude by discussing the significance of these patterns beyond the security of the specific providers.