Exponential growth in embedded systems is driving the research imperative to develop fuzzers to automate firmware testing to uncover software bugs and security vulnerabilities. But, employing fuzzing techniques in this context present a uniquely challenging proposition; a key problem is the need to deal with the diverse and large number of peripheral communications in an automated testing framework. Recent fuzzing approaches: i) employ re-hosting methods by executing code in an emulator because fuzzing on resource limited embedded systems is slow and unscalable; and ii) integrate models of hardware behaviour to overcome the challenges faced by the massive input-space to be explored created by peripheral devices and to generate inputs that are effective in aiding a fuzzer to make progress.