Negative testing addresses the crucial issue of determining a system's capacity to deal with unforeseen circumstances. If left unattended, such circumstances may result in system failures that, in certain cases, may have catastrophic effects. In order to generate test cases that support negative testing, this paper provides a mutation testing-based methodology. Application of this strategy can deliver test cases that successfully evaluate a wide range of unexpected circumstances in a methodical and human-unbiased manner. As a result, it can help a tested system improve. The article offers a general architecture for the production and execution of the test cases, explicitly specifies mutation operators used to manage the generation process, and discusses how to analyse results.