The rapid growth of the Internet has triggered an explosion in the number of applications that leverage its capabilities. Unfortunately, many are designed to burden o infrastructure. Hence, considerable effort has been focused on detecting and predicting the security breaches they propagate. However, the enormity of the Internet poses a formidable challenge to analyzing such attacks using scalable models. Furthermore, the lack of complete information on network vulnerabilities makes forecasting the systems that may be exploited by such applications in the future very hard. This paper presents a technique for deriving a scalable model for representing network attacks, and its application to identify actual attacks with greater certainty amongst false positives and false negatives. It also presents a method to forecast the propagation of security failures proliferated by an attack over time and its likely targets in the future.