Software defects rediscovered by a large number of customers affect various stakeholders and may: 1) hint at gaps in a software manufacturer's Quality Assurance (QA) processes, 2) lead to an over-load of a software manufacturer's support and maintenance teams, and 3) consume customers' resources, leading to a loss of reputation and a decrease in sales. Quantifying risk associated with the rediscovery of defects can help all of these stake-holders. In this chapter we present a set of metrics needed to quantify the risks. The metrics are designed to help: 1) the QA team to assess their processes; 2) the support and maintenance teams to allocate their resources; and 3) the customers to assess the risk associated with using the software product. The paper includes a validation case study which applies the risk metrics to industrial data. To calculate the metrics we use mathematical instruments like the heavy-tailed Kappa distribution and the G/M/k queuing model.