We introduce a new simulation platform called Insight, created to design and simulate cyber-attacks against large arbitrary target scenarios. Insight has surprisingly low hardware and configuration requirements, while making the simulation a realistic experience from the attacker's standpoint. The scenarios include a crowd of simulated actors: network devices, hardware devices, software applications, protocols, users, etc. A novel characteristic of this tool is to simulate vulnerabilities (including 0-days) and exploits, allowing an attacker to compromise machines and use them as pivoting stones to continue the attack. A user can test and modify complex scenarios, with several interconnected networks, where the attacker has no initial connectivity with the objective of the attack. We give a concise description of this new technology, and its possible uses in the security research field, such as pentesting training, study of the impact of 0-days vulnerabilities, evaluation of security countermeasures, and risk assessment tool.
In contrast, high interaction honeypots'' and virtualization technologies (e.g., VMware, Xen, Qemu) execute native system and application code, but the price of this fidelity is quite high. For example, the RINSE approach @cite_9 is implemented over the iSSFNet network simulator, which runs on parallel machines to support real-time simulation of large-scale networks. All these solutions share the same principle of simulating almost every aspect of a real machine or real network, but share the similar problems too: expensive configuration cost and expensive hardware and software licenses. Moreover, most of these solutions are not fully compatible with standard network protections (e.g., firewalls, IDSs), suffering a lack of integration between all security actors in complex cyber-attack scenarios.
@cite_9
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Virtual Machine (VM) environments (e.g., VMware and Xen) are experiencing a resurgence of interest for diverse uses including server consolidation and shared hosting. An application's performance in a virtual machine environment can differ markedly from its performance in a non-virtualized environment because of interactions with the underlying virtual machine monitor and other virtual machines. However, few tools are currently available to help debug performance problems in virtual machine environments.In this paper, we present Xenoprof, a system-wide statistical profiling toolkit implemented for the Xen virtual machine environment. The toolkit enables coordinated profiling of multiple VMs in a system to obtain the distribution of hardware events such as clock cycles and cache and TLB misses. The toolkit will facilitate a better understanding of performance characteristics of Xen's mechanisms allowing the community to optimize the Xen implementation.We use our toolkit to analyze performance overheads incurred by networking applications running in Xen VMs. We focus on networking applications since virtualizing network I O devices is relatively expensive. Our experimental results quantify Xen's performance overheads for network I O device virtualization in uni- and multi-processor systems. With certain Xen configurations, networking workloads in the Xen environment can suffer significant performance degradation. Our results identify the main sources of this overhead which should be the focus of Xen optimization efforts. We also show how our profiling toolkit was used to uncover and resolve performance bugs that we encountered in our experiments which caused unexpected application behavi