The existing tools for testing spam filters evaluate a filter instance by simply feeding it with a stream of emails, possibly also providing a feedback to the filter about the correctness of the detection. In such a scenario the evaluated filter is disconnected from the network of email servers, filters, and users, which makes the approach inappropriate for testing many of the filters that exploit some of the information about spam bulkiness, users' actions and social relations among the users. Corresponding evaluation results might be wrong, because the information that is normally used by the filter is missing, incomplete or inappropriate. In this paper we present a tool for testing spam filters in a very realistic scenario. Our tool consists of a set of Python scripts for unix/linux environment. The tool takes as inputs the filter to be tested and an affordable set of interconnected machines (e.g., PlanetLab machines, or locally created virtual machines). When started from a central place, the tool uses the provided machines to build a network of real email servers, installs instances of the filter, deploys and runs simulated email users and spammers, and computes the detection results statistic. Email servers are implemented using Postfix, a standard linux email server. Only per-email-server filters are currently supported, whereas per-email-client filters testing would require additional tool development. The size of the created emailing network is constrained only by the number of available PlanetLab or virtual machines. The run time is much shorter then the simulated system time, due to a time scaling mechanism. Testing a new filter is as simple as installing one copy of it in a real emailing network, which unifies the jobs of a new filter development, testing and prototyping. As a usage example, we test the SpamAssassin filter
