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.
The @cite_17 is another interesting prototype. It improves high-fidelity honeypot scalability by up to six times while still closely emulating the execution behavior of individual Internet hosts. Potemkin uses quite sophisticated on-demand techniques for instantiating hosts Including file system optimizations implemented also in , as we are going to see it in . , but this approach focuses on attracting real attacks and it shows the same honeypot limitations to reach this goal. As an example, to capture e-mail viruses, a honeypot must posses an e-mail address, must be scripted to read mail (executing attachments like a naive user) and, most critically, must be influenced to add the honeypot to their address books. Passive malware (e.g., many spyware applications) may require a honeypot to generate explicit requests, and focused malware (e.g., targeting only financial institutions) may carefully select its victims and never touch a large-scale honeyfarm. In each of these cases there are partial solutions, and they require careful engineering to truly mimic the target environment.
@cite_17
1514368868
The rapid evolution of large-scale worms, viruses and bot-nets have made Internet malware a pressing concern. Such infections are at the root of modern scourges including DDoS extortion, on-line identity theft, SPAM, phishing, and piracy. However, the most widely used tools for gathering intelligence on new malware -- network honeypots -- have forced investigators to choose between monitoring activity at a large scale or capturing behavior with high fidelity. In this paper, we describe an approach to minimize this tension and improve honeypot scalability by up to six orders of magnitude while still closely emulating the execution behavior of individual Internet hosts. We have built a prototype honeyfarm system, called Potemkin, that exploits virtual machines, aggressive memory sharing, and late binding of resources to achieve this goal. While still an immature implementation, Potemkin has emulated over 64,000 Internet honeypots in live test runs, using only a handful of physical servers.