Water supply systems face dynamic and complex challenges, from control device malfunctions and fluctuating demand to infrastructure failures, all of which may threaten consumer access. Assessing Water Distribution Network (WDN) resilience is essential for mitigating these impacts. Contamination risks from sources such as pipe cracks and backflow endanger public health and system integrity. Understanding contamination pathways requires analyzing factors like contaminant sources, pressure variations, and structural vulnerabilities such as cross-connections. Pinpointing critical nodes prone to contaminant spread is key to effective risk management. This study uses Complex Network Theory (CNT) to explore the efficacy of network metrics in identifying high-risk zones. Comparing CNT-derived metrics with hydraulic simulations highlights nodes that accelerate rapid contaminant propagation. By integrating CNT with risk analysis methodologies, this research enhances the understanding of WDN vulnerabilities and aids decision-making for ensuring water quality and supply reliability.