As critical infrastructures continuously put efforts to enhance cyber security and safeguarding their critical assets, cyber threats evolve in complexity, seeking new vulnerabilities to exploit. Electric vehicles (EV) charging stations are important components of the smart grid, making them targets for cyber attacks that could disrupt service availability. Therefore, it is crucial to implement efficient detection and continuous monitoring systems. This study investigates the detection of heartbeat flood attacks aimed at overwhelming the central asset of a EV charging stations using the Montimage Monitoring Tool (MMT). We define attack scenarios using event-based properties, which are then integrated into MMT to analyze both real and simulated traffic for effective detection and mitigation of these attacks. Findings show that the proposed approach successfully identifies Heartbeat flood attacks, distinguishing between normal and malicious traffic patterns demonstrating the potential of integrating formal methods into monitoring tools to enhance resilience in EV charging station systems.