This paper introduces RESTler, the first stateful REST API fuzzer. RESTler analyzes the API specification of a cloud service and generates sequences of requests that automatically test the service through its API. RESTler generates test sequences by (1) inferring producer-consumer dependencies among request types declared in the specification (e.g., inferring that \u201ca request B should be executed after request A\u201d because B takes as an input a resource-id x produced by A) and by (2) analyzing dynamic feedback from responses observed during prior test executions in order to generate new tests (e.g., learning that \u201ca request C after a request sequence A;B is refused by the service\u201d and therefore avoiding this combination in the future). We present experimental results showing that these two techniques are necessary to thoroughly exercise a service under test while pruning the large search space of possible request sequences. We used RESTler to test GitLab, an open-source Git service, as well as several Microsoft Azure and Office365 cloud services. RESTler found 28 bugs in GitLab and several bugs in each of the Azure and Office365 cloud services tested so far. These bugs have been confirmed and fixed by the service owners.<\/p>\n","protected":false},"excerpt":{"rendered":"
This paper introduces RESTler, the first stateful REST API fuzzer. RESTler analyzes the API specification of a cloud service and generates sequences of requests that automatically test the service through its API. RESTler generates test sequences by (1) inferring producer-consumer dependencies among request types declared in the specification (e.g., inferring that \u201ca request B should 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