Outlook Magazine, Autumn 2014

https://digitalcommons.wustl.edu/outlook/1193/thumbnail.jp

On the detection of virtual machine introspection from inside a guest virtual machine

Thesis (Ph.D.) University of Alaska Fairbanks, 2015With the increased prevalence of virtualization in the modern computing environment, the security of that technology becomes of paramount importance. Virtual Machine Introspection (VMI) is one of the technologies that has emerged to provide security for virtual environments by examining and then interpreting the state of an active Virtual Machine (VM). VMI has seen use in systems administration, digital forensics, intrusion detection, and honeypots. As with any technology, VMI has both productive uses as well as harmful uses. The research presented in this dissertation aims to enable a guest VM to determine if it is under examination by an external VMI agent. To determine if a VM is under examination a series of statistical analyses are performed on timing data generated by the guest itself

Cross-VM Network Channel Attacks and Countermeasures within Cloud Computing Environments

Cloud providers attempt to maintain the highest levels of isolation between Virtual Machines (VMs) and inter-user processes to keep co-located VMs and processes separate. This logical isolation creates an internal virtual network to separate VMs co-residing within a shared physical network. However, as co-residing VMs share their underlying VMM (Virtual Machine Monitor), virtual network, and hardware are susceptible to cross VM attacks. It is possible for a malicious VM to potentially access or control other VMs through network connections, shared memory, other shared resources, or by gaining the privilege level of its non-root machine. This research presents a two novel zero-day cross-VM network channel attacks. In the first attack, a malicious VM can redirect the network traffic of target VMs to a specific destination by impersonating the Virtual Network Interface Controller (VNIC). The malicious VM can extract the decrypted information from target VMs by using open source decryption tools such as Aircrack. The second contribution of this research is a privilege escalation attack in a cross VM cloud environment with Xen hypervisor. An adversary having limited privileges rights may execute Return-Oriented Programming (ROP), establish a connection with the root domain by exploiting the network channel, and acquiring the tool stack (root domain) which it is not authorized to access directly. Countermeasures against this attacks are also presente

Cloud-Trust - A Security Assessment Model for Infrastructure as a Service (IaaS) Clouds

The vulnerability of Cloud Computing Systems (CCSs) to Advanced Persistent Threats (APTs) is a significant concern to government and industry. We present a cloud architecture reference model that incorporates a wide range of security controls and best practices, and a cloud security assessment model – Cloud-Trust – that estimates high level security metrics to quantify the degree of confidentiality and integrity offered by a CCS or cloud service provider (CSP). Cloud-Trust is used to assess the security level of four multi-tenant IaaS cloud architectures equipped with alternative cloud security controls and to show the probability of CCS penetration (high value data compromise) is high if a minimal set of security controls are implemented. CCS penetration probability drops substantially if a cloud defense in depth security architecture is adopted that protects virtual machine (VM) images at rest, strengthens CSP and cloud tenant system administrator access controls, and which employs other network security controls to minimize cloud network surveillance and discovery of live VMs

Discovering New Vulnerabilities in Computer Systems

Vulnerability research plays a key role in preventing and defending against malicious computer system exploitations. Driven by a multi-billion dollar underground economy, cyber criminals today tirelessly launch malicious exploitations, threatening every aspect of daily computing. to effectively protect computer systems from devastation, it is imperative to discover and mitigate vulnerabilities before they fall into the offensive parties\u27 hands. This dissertation is dedicated to the research and discovery of new design and deployment vulnerabilities in three very different types of computer systems.;The first vulnerability is found in the automatic malicious binary (malware) detection system. Binary analysis, a central piece of technology for malware detection, are divided into two classes, static analysis and dynamic analysis. State-of-the-art detection systems employ both classes of analyses to complement each other\u27s strengths and weaknesses for improved detection results. However, we found that the commonly seen design patterns may suffer from evasion attacks. We demonstrate attacks on the vulnerabilities by designing and implementing a novel binary obfuscation technique.;The second vulnerability is located in the design of server system power management. Technological advancements have improved server system power efficiency and facilitated energy proportional computing. However, the change of power profile makes the power consumption subjected to unaudited influences of remote parties, leaving the server systems vulnerable to energy-targeted malicious exploit. We demonstrate an energy abusing attack on a standalone open Web server, measure the extent of the damage, and present a preliminary defense strategy.;The third vulnerability is discovered in the application of server virtualization technologies. Server virtualization greatly benefits today\u27s data centers and brings pervasive cloud computing a step closer to the general public. However, the practice of physical co-hosting virtual machines with different security privileges risks introducing covert channels that seriously threaten the information security in the cloud. We study the construction of high-bandwidth covert channels via the memory sub-system, and show a practical exploit of cross-virtual-machine covert channels on virtualized x86 platforms