The notion of adversary is a staple of distributed computing. An adversary typically models hostile assumptions about the underlying distributed environment, e.g., a network that can drop messages, an operating system that can delay processes or an attacker that can hack machines. So far, the goal of distributed computing researchers has mainly been to develop a distributed algorithm that can face a given adversary, the abstraction characterizing worst-case scenarios. This paper initiates the study of the somehow opposite approach. Given a distributed algorithm, the adversary is the abstraction we seek to implement. More specifically, we consider the problem of controlling the spread of messages in a large- scale system, conveying the practical motivation of limiting the dissemination of fake news or viruses. Essentially, we assume a general class of gossip protocols, called all-to-all gossip protocols, and devise a practical method to hinder the dissemination. We present the Universal Gossip Fighter (UGF). Just like classical adversaries in distributed computing, UGF can observe the status of a dissemination and decide to stop some processes or delay some messages. The originality of UGF lies in the fact that it is universal, i.e., it applies to any all-to-all gossip protocol. We show that any gossip protocol attacked by UGF ends up exhibiting a quadratic message complexity (in the total number of processes) if it achieves sublinear time of dissemination. We also show that if a gossip protocol aims to achieve a message complexity α times smaller than quadratic, then the time complexity rises exponentially in relation to α. We convey the practical relevance of our theoretical findings by implementing UGF and conducting a set of empirical experiments that confirm some of our results.