  Software's pervasive impact and increasing reliance in the era of digital
transformation raise concerns about vulnerabilities, emphasizing the need for
software security. Fuzzy testing is a dynamic analysis software testing
technique that consists of feeding faulty input data to a System Under Test
(SUT) and observing its behavior. Specifically regarding black-box RESTful API
testing, recent literature has attempted to automate this technique using
heuristics to perform the input search and using the HTTP response status codes
for classification. However, most approaches do not keep track of code
coverage, which is important to validate the solution. This work introduces a
black-box RESTful API fuzzy testing tool that employs Reinforcement Learning
(RL) for vulnerability detection. The fuzzer operates via the OpenAPI
Specification (OAS) file and a scenarios file, which includes information to
communicate with the SUT and the sequences of functionalities to test,
respectively. To evaluate its effectiveness, the tool was tested on the
Petstore API. The tool found a total of six unique vulnerabilities and achieved
55\% code coverage.
