Biblio

Virtual switches are a crucial component of SDN-based cloud systems, enabling the interconnection of virtual machines in a flexible and "software-defined" manner. This paper raises the alarm on the security implications of virtual switches. In particular, we show that virtual switches not only increase the attack surface of the cloud, but virtual switch vulnerabilities can also lead to attacks of much higher impact compared to traditional switches. We present a systematic security analysis and identify four design decisions which introduce vulnerabilities. Our findings motivate us to revisit existing threat models for SDN-based cloud setups, and introduce a new attacker model for SDN-based cloud systems using virtual switches. We demonstrate the practical relevance of our analysis using a case study with Open vSwitch and OpenStack. Employing a fuzzing methodology, we find several exploitable vulnerabilities in Open vSwitch. Using just one vulnerability we were able to create a worm that can compromise hundreds of servers in a matter of minutes. Our findings are applicable beyond virtual switches: NFV and high-performance fast path implementations face similar issues. This paper also studies various mitigation techniques and discusses how to redesign virtual switches for their integration.

Networks are vulnerable to disruptions caused by malicious forwarding devices. The situation is likely to worsen in Software Defined Networks (SDNs) with the incompatibility of existing solutions, use of programmable soft switches and the potential of bringing down an entire network through compromised forwarding devices. In this paper, we present WedgeTail, an Intrusion Prevention System (IPS) designed to secure the SDN data plane. WedgeTail regards forwarding devices as points within a geometric space and stores the path packets take when traversing the network as trajectories. To be efficient, it prioritizes forwarding devices before inspection using an unsupervised trajectory-based sampling mechanism. For each of the forwarding device, WedgeTail computes the expected and actual trajectories of packets and 'hunts' for any forwarding device not processing packets as expected. Compared to related work, WedgeTail is also capable of distinguishing between malicious actions such as packet drop and generation. Moreover, WedgeTail employs a radically different methodology that enables detecting threats autonomously. In fact, it has no reliance on pre-defined rules by an administrator and may be easily imported to protect SDN networks with different setups, forwarding devices, and controllers. We have evaluated WedgeTail in simulated environments, and it has been capable of detecting and responding to all implanted malicious forwarding devices within a reasonable time-frame. We report on the design, implementation, and evaluation of WedgeTail in this manuscript.