As power grids evolve into more intelligent and interconnected systems, their vulnerability to cyber-attacks has become a pressing concern. This thesis investigates the resilience of smart grid infrastructure under two major types of cyber threats: False Data Injection (FDI) and Denial of services (DoS). Using the IEEE 14-bus system as a representative testbed, a simulation framework was developed in Python with Pandapower to emulate these attack scenarios. Through systematic testing, performance metrics such as Time to Compromise (TTC), Time to Recovery (TTR), Power Loss, and Percentage Load Served were captured and analyzed. The findings reveal distinct differences in how integrity-and availability-focused attacks affect grid performance. While FDI attacks cause moderate disruptions due to misleading data, DoS attacks can severely destabilize the grid by blocking communication and delaying mitigation. The study also demonstrates the utility of basic countermeasures like voltage threshold-based SCADA logic and rudimentary IDS in improving system resilience. Ultimately, this research offers a practical methodology for assessing and enhancing the cybersecurity posture of modern power grids, laying the groundwork for more adaptive and robust defense mechanisms in future energy systems