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Modern agriculture is reliant on agricultural machinery for the production of food, fuel, and other agricultural products. The need for producing large quantities of quality agricultural products while sustainably stewarding environmental resources has led to the integration of numerous digital technologies into modern agricultural machinery, such as the CAN bus and telematic control units (Liu et al., 2021). An unintended drawback of these integrated digital technologies is the opportunity for these components to become cyberattack vectors. Cyberattack instances have increasingly targeted critical infrastructures, with numerous reports from agencies such as the Federal Bureau of Investigation (FBI) and Department of Homeland Security (DHS) warning of the significance of cyberattacks targeting the agricultural infrastructure specifically (Boghossian et al., 2018; Federal Bureau of Investigation, 2021; Federal Bureau of Investigation, 2022). Agricultural machinery, which is included in the agricultural infrastructure, has the potential to be targeted by cyberattacks, although the impacts are not well quantified or understood. This project demonstrates a hypothetical case study, where cyberattacks targeting in-season side-dress nitrogen application to corn could cause as much as $100 or more in profit loss per acre. Literature discussing practical cybersecurity solutions for agricultural machinery from both industry and academic institutions is absent, therefore two possible solutions were demonstrated in this project: modeling and the use of security testbeds. A four-step modeling methodology was developed and investigated as a solution in identifying the most security-critical areas of a machine. Two specific cyberattack scenarios were modeled to demonstrate the potential of the modeling methodology. A Security Testbed for Agricultural Vehicles and Environments (STAVE) was also developed as a useful solution for the identification of cybersecurity vulnerabilities to agricultural machinery (Freyhof et al., 2022). A replay attack and wireless signal recordings were performed to evaluate various components on STAVE. Advisor: Santosh K. Pitla