MQTT's security has been a major concern because of its weak protocol implementations. Over the last few years, several fuzzing frameworks have been proposed to mitigate this issue. However, these frameworks lack sufficient knowledge of MQTT's specifications, requiring a considerable amount of network packets to cover all of its features and functionality. In this paper, we explain how to improve the efficiency of fuzzing frameworks for MQTT by using a grammar based on its specifications. Although defining a grammar is time-consuming and complex, these drawbacks are overshadowed by its benefits, such as deep state exploration and efficiency. Our improvements are implemented in MQTTGRAM, a new grammar-based fuzzer for MQTT. Due to these improvements, MQTTGRAM offers higher code coverage with significantly fewer packets than existing MQTT fuzzers. For instance, MQTTGRAM exchanges up to 9x fewer packets than its counterparts without reducing the line coverage.

Over the last few years, MQTT applications have been widely exposed to vulnerabilities because of their weak protocol implementations. For our preliminary research, we conducted background studies to: (1) determine the main cause of vulnerabilities in MQTT applications; and (2) analyze existing MQTT-based testing frameworks. Our preliminary results confirm that MQTT is most susceptible to malformed packets, and its existing testing frameworks are based on blackbox fuzzing, meaning vulnerabilities are difficult and time-consuming to find. Thus, the aim of my research is to study and develop effective fuzzing strategies for the MQTT protocol, thereby contributing to the development of more robust MQTT applications in IoT and Smart Cities.