Operating systems are difficult to debug with traditional cyclic debugging. They are non-deterministic; they run for long periods of time; they interact directly with hardware devices; and their state is easily perturbed by the act of debugging. This paper describes a time-traveling virtual machine that overcomes many of the difficulties associated with debugging operating systems. Time travel enables a programmer to navigate backward and forward arbitrarily through the execution history of a particular run and to replay arbitrary segments of the past execution. We integrate time travel into a general-purpose debugger to enable a programmer to debug an OS in reverse, implementing commands such as reverse breakpoint, reverse watchpoint, and reverse single step. The space and time overheads needed to support time travel are reasonable for debugging, and movements in time are fast enough to support interactive debugging. We demonstrate the value of our time-traveling virtual machine by using it to understand and fix several OS bugs that are difficult to find with standard debugging tools. Reverse debugging is especially helpful in finding bugs that are fragile due to non-determinism, bugs in device drivers, bugs that require long runs to trigger, bugs that corrupt the stack, and bugs that are detected after the relevant stack frame is popped. 1

The Xen virtual machine monitor allows multiple operating systems to execute concurrently on commodity x86 hardware, providing a solution for server consolidation and utility computing. In our initial design, Xen itself contained device-driver code and provided safe shared virtual device access. In this paper we present our new Safe Hardware Interface, an isolation architecture used within the latest release of Xen which allows unmodified device drivers to be shared across isolated operating system instances, while protecting individual OSs, and the system as a whole, from driver failure. 1

Attackers and defenders of computer systems both strive to gain complete control over the system. To maximize their control, both attackers and defenders have migrated to low-level, operating system code. In this paper, we assume the perspective of the attacker, who is trying to run malicious software and avoid detection. By assuming this perspective, we hope to help defenders understand and defend against the threat posed by a new class of rootkits. We evaluate a new type of malicious software that gains qualitatively more control over a system. This new type of malware, which we call a virtual-machine based rootkit (VMBR), installs a virtual-machine monitor underneath an existing operating system and hoists the original operating system into a virtual machine. Virtual-machine based rootkits are hard to detect and remove because their state cannot be accessed by software running in the target system. Further, VMBRs support general-purpose malicious services by allowing such services to run in a separate operating system that is protected from the target system. We evaluate this new threat by implementing two proof-of-concept VMBRs. We use our proof-of-concept VMBRs to subvert Windows XP and Linux target systems, and we implement four example malicious services using the VMBR platform. Last, we use what we learn from our proof-of-concept VMBRs to explore ways to defend against this new threat. We discuss possible ways to detect and prevent VMBRs, and we implement a defense strategy suitable for protecting systems against this threat. 1.

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 nonvirtualized 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. 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. 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 behavior.

We present SafeDrive, a system for detecting and recovering from type safety violations in software extensions. SafeDrive has low overhead and requires minimal changes to existing source code. To achieve this result, SafeDrive uses a novel type system that provides finegrained isolation for existing extensions written in C. In addition, SafeDrive tracks invariants using simple wrappers for the host system API and restores them when recovering from a violation. This approach achieves finegrained memory error detection and recovery with few code changes and at a significantly lower performance cost than existing solutions based on hardware-enforced domains, such as Nooks [33], L4 [21], and Xen [13], or software-enforced domains, such as SFI [35]. The principles used in SafeDrive can be applied to any large system with loadable, error-prone extension modules. In this paper we describe our experience using SafeDrive for protection and recovery of a variety of Linux device drivers. In order to apply SafeDrive to these device drivers, we had to change less than 4 % of the source code. SafeDrive recovered from all 44 crashes due to injected faults in a network card driver. In experiments with 6 different drivers, we observed increases in kernel CPU utilization of 4–23 % with no noticeable degradation in end-to-end performance. 1

The trusted computing bases (TCBs) of applications running on today’s commodity operating systems have become extremely large. This paper presents an architecture that allows to build applications with a much smaller TCB. It is based on a kernelized architecture and on the reuse of legacy software using trusted wrappers. We discuss the design principles, the architecture and some components, and a number of usage examples. 1

Current approaches to power management are based on operating systems with full knowledge of and full control over the underlying hardware; the distributed nature of multi-layered virtual machine environments renders such approaches insufficient. In this paper, we present a novel framework for energy management in modular, multi-layered operating system structures. The framework provides a unified model to partition and distribute energy, and mechanisms for energy-aware resource accounting and allocation. As a key property, the framework explicitly takes the recursive energy consumption into account, which is spent, e.g., in the virtualization layer or subsequent driver components. Our prototypical implementation targets hypervisor-based virtual machine systems and comprises two components: a host-level subsystem, which controls machine-wide energy constraints and enforces them among all guest OSes and service components, and, complementary, an energy-aware guest operating system, capable of fine-grained applicationspecific energy management. Guest level energy management thereby relies on effective virtualization of physical energy effects provided by the virtual machine monitor. Experiments with CPU and disk devices and an external data acquisition system demonstrate that our framework accurately controls and stipulates the power consumption of individual hardware devices, both for energy-aware and energyunaware guest operating systems. 1

Device drivers commonly execute in the kernel to achieve high performance and easy access to kernel services. However, this comes at the price of decreased reliability and increased programming difficulty. Driver programmers are unable to use user-mode development tools and must instead use cumbersome kernel tools. Faults in kernel drivers can cause the entire operating system to crash. Usermode drivers have long been seen as a solution to this problem, but suffer from either poor performance or new interfaces that require a rewrite of existing drivers. This paper introduces the Microdrivers architecture that achieves high performance and compatibility by leaving critical path code in the kernel and moving the rest of the driver code to a user-mode process. This allows data-handling operations critical to I/O performance to run at full speed, while management operations such as initialization and configuration run at reduced speed in userlevel. To achieve compatibility, we present DriverSlicer, a tool that splits existing kernel drivers into a kernel-level component and a user-level component using a small number of programmer annotations. Experiments show that as much as 65 % of driver code can be removed from the kernel without affecting common-case performance, and that only 1-6 percent of the code requires annotations.

When was the last time your TV set crashed or implored you to download some emergency software update from the Web? After all, unless it is an ancient set, it is just a computer with a CPU, a big monitor, some analog electronics for decoding radio signals, a couple of peculiar I/O devices (e.g., remote control, built in VCR or DVD drive) and a boatload of software in ROM. This rhetorical question points out a nasty little secret that we in the computer industry do not like to discuss: why are TV sets, DVD recorders, MP3 players, cell phones, and other software-laden electronic devices reliable and secure and computers not? Of course there are many ‘reasons ’ (computers are flexible, users can change the software, the

Bugs in kernel extensions remain one of the main causes of poor operating system reliability despite proposed techniques that isolate extensions in separate protection domains to contain faults. We believe that previous fault isolation techniques are not widely used because they cannot isolate existing kernel extensions with low overhead on standard hardware. This is a hard problem because these extensions communicate with the kernel using a complex interface and they communicate frequently. We present BGI (Byte-Granularity Isolation), a new software fault isolation technique that addresses this problem. BGI uses efficient byte-granularity memory protection to isolate kernel extensions in separate protection domains that share the same address space. BGI ensures type safety for kernel objects and it can detect common types of errors inside domains. Our results show that BGI is practical: it can isolate Windows drivers without requiring changes to the source code and it introduces a CPU overhead between 0 and 16%. BGI can also find bugs during driver testing. We found 28 new bugs in widely used Windows drivers.