Supply chains are becoming more global, complex and increasingly vulnerable. Specifically, the latest evolution of the modern supply chains creates crucial cyber-risks and cyber-security challenges. Nowadays, supply chain risk managers need methods and tools for control, analysis, risk mitigation and managing of their cyber vulnerabilities. In this context, cyber-risk modeling and analysis in supply chain has become one of the major research subjects. The first part of this chapter provides a survey of the field and investigates the use of Petri Nets as a tool for modeling and performance analysis of supply chains, as well as their great potential for supply chain risk analysis. The second part of this work is dedicated to our contributions for modeling and performance evaluation of supply chain networks by using discrete event dynamic approaches. Based on the modeling and performance analysis power of Batch Deterministic and Stochastic Petri nets (BDSPN) for supply chain and logistic systems, two original risk-modeling approaches are introduced for this emerging research topic.