Unikernels: the Next Stage of Linux's Dominance
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Intra-Unikernel Isolation with Intel Memory Protection Keys
Intra-Unikernel Isolation with Intel Memory Protection Keys Mincheol Sung Pierre Olivier∗ Virginia Tech, USA The University of Manchester, United Kingdom [email protected] [email protected] Stefan Lankes Binoy Ravindran RWTH Aachen University, Germany Virginia Tech, USA [email protected] [email protected] Abstract ACM Reference Format: Mincheol Sung, Pierre Olivier, Stefan Lankes, and Binoy Ravin- Unikernels are minimal, single-purpose virtual machines. dran. 2020. Intra-Unikernel Isolation with Intel Memory Protec- This new operating system model promises numerous bene- tion Keys. In 16th ACM SIGPLAN/SIGOPS International Conference fits within many application domains in terms of lightweight- on Virtual Execution Environments (VEE ’20), March 17, 2020, Lau- ness, performance, and security. Although the isolation be- sanne, Switzerland. ACM, New York, NY, USA, 14 pages. https: tween unikernels is generally recognized as strong, there //doi.org/10.1145/3381052.3381326 is no isolation within a unikernel itself. This is due to the use of a single, unprotected address space, a basic principle 1 Introduction of unikernels that provide their lightweightness and perfor- Unikernels have gained attention in the academic research mance benefits. In this paper, we propose a new design that community, offering multiple benefits in terms of improved brings memory isolation inside a unikernel instance while performance, increased security, reduced costs, etc. As a keeping a single address space. We leverage Intel’s Memory result, -
A Linux in Unikernel Clothing Lupine
A Linux in Unikernel Clothing Hsuan-Chi Kuo+, Dan Williams*, Ricardo Koller* and Sibin Mohan+ +University of Illinois at Urbana-Champaign *IBM Research Lupine Unikernels are great BUT: Unikernels lack full Linux Support App ● Hermitux: supports only 97 system calls Kernel LibOS + App ● OSv: ○ Fork() , execve() are not supported Hypervisor Hypervisor ○ Special files are not supported such as /proc ○ Signal mechanism is not complete ● Small kernel size ● Rumprun: only 37 curated applications ● Heavy ● Fast boot time ● Community is too small to keep it rolling ● Inefficient ● Improved performance ● Better security 2 Can Linux behave like a unikernel? 3 Lupine Linux 4 Lupine Linux ● Kernel mode Linux (KML) ○ Enables normal user process to run in kernel mode ○ Processes can still use system services such as paging and scheduling ○ App calls kernel routines directly without privilege transition costs ● Minimal patch to libc ○ Replace syscall instruction to call ○ The address of the called function is exported by the patched KML kernel using the vsyscall ○ No application changes/recompilation required 5 Boot time Evaluation Metrics Image size Based on: Unikernel benefits Memory footprint Application performance Syscall overhead 6 Configuration diversity ● 20 top apps on Docker hub (83% of all downloads) ● Only 19 configuration options required to run all 20 applications: lupine-general 7 Evaluation - Comparison configurations Lupine Cloud Operating Systems [Lupine-base + app-specific options] OSv general Linux-based Unikernels Kernel for 20 apps -
Unikernel Monitors: Extending Minimalism Outside of the Box
Unikernel Monitors: Extending Minimalism Outside of the Box Dan Williams Ricardo Koller IBM T.J. Watson Research Center Abstract Recently, unikernels have emerged as an exploration of minimalist software stacks to improve the security of ap- plications in the cloud. In this paper, we propose ex- tending the notion of minimalism beyond an individual virtual machine to include the underlying monitor and the interface it exposes. We propose unikernel monitors. Each unikernel is bundled with a tiny, specialized mon- itor that only contains what the unikernel needs both in terms of interface and implementation. Unikernel mon- itors improve isolation through minimal interfaces, re- Figure 1: The unit of execution in the cloud as (a) a duce complexity, and boot unikernels quickly. Our ini- unikernel, built from only what it needs, running on a tial prototype, ukvm, is less than 5% the code size of a VM abstraction; or (b) a unikernel running on a spe- traditional monitor, and boots MirageOS unikernels in as cialized unikernel monitor implementing only what the little as 10ms (8× faster than a traditional monitor). unikernel needs. 1 Introduction the application (unikernel) and the rest of the system, as defined by the virtual hardware abstraction, minimal? Minimal software stacks are changing the way we think Can application dependencies be tracked through the in- about assembling applications for the cloud. A minimal terface and even define a minimal virtual machine mon- amount of software implies a reduced attack surface and itor (or in this case a unikernel monitor) for the applica- a better understanding of the system, leading to increased tion, thus producing a maximally isolated, minimal exe- security. -
Assessing Unikernel Security April 2, 2019 – Version 1.0
NCC Group Whitepaper Assessing Unikernel Security April 2, 2019 – Version 1.0 Prepared by Spencer Michaels Jeff Dileo Abstract Unikernels are small, specialized, single-address-space machine images constructed by treating component applications and drivers like libraries and compiling them, along with a kernel and a thin OS layer, into a single binary blob. Proponents of unikernels claim that their smaller codebase and lack of excess services make them more efficient and secure than full-OS virtual machines and containers. We surveyed two major unikernels, Rumprun and IncludeOS, and found that this was decidedly not the case: unikernels, which in many ways resemble embedded systems, appear to have a similarly minimal level of security. Features like ASLR, W^X, stack canaries, heap integrity checks and more are either completely absent or seriously flawed. If an application running on such a system contains a memory corruption vulnerability, it is often possible for attackers to gain code execution, even in cases where the applica- tion’s source and binary are unknown. Furthermore, because the application and the kernel run together as a single process, an attacker who compromises a unikernel can immediately exploit functionality that would require privilege escalation on a regular OS, e.g. arbitrary packet I/O. We demonstrate such attacks on both Rumprun and IncludeOS unikernels, and recommend measures to mitigate them. Table of Contents 1 Introduction to Unikernels . 4 2 Threat Model Considerations . 5 2.1 Unikernel Capabilities ................................................................ 5 2.2 Unikernels Versus Containers .......................................................... 5 3 Hypothesis . 6 4 Testing Methodology . 7 4.1 ASLR ................................................................................ 7 4.2 Page Protections .................................................................... -
“A Linux in Unikernel Clothing”
Lupine Linux “A Linux in Unikernel Clothing” Dan Williams (IBM) With Hsuan-Chi (Austin) Kuo (UIUC + IBM), Ricardo Koller (IBM), Sibin Mohan (UIUC) Roadmap • Context • Containers and isolation • Unikernels • Nabla containers • Lupine Linux • A linux in unikernel clothing • Concluding thoughts 2 Containers are great! • Have changed how applications are packaged, deployed and developed • Normal processes, but “contained” • Namespaces, cgroups, chroot • Lightweight • Start quickly, “bare metal” • Easy image management (layered fs) • Tooling/orchestration ecosystem 3 But… High level of • Large attack surface to the host abstraction (e.g., system • Limits adoption of container-first architecture calls) app • Fortunately, we know how to reduce attack surface! Host Kernel with namespacing (e.g., Linux) Containers 4 Deprivileging and unsharing kernel functionality Low level of High level of • Virtual machines (VMs) abstraction abstraction • Guest kernel (e.g., virtual (e.g., system app hardware) calls) • Thin interface Guest Kernel app (e.g., Linux) Monitor Process (e.g., QEMU) Host Kernel with Host Kernel/Hypervisor namespacing (e.g., Linux/KVM) (e.g., Linux) VMs Containers 5 Deprivileging and unsharing kernel functionality Low level of High level of • Virtual machines (VMs) abstraction abstraction • Guest kernel (e.g., virtual (e.g., system app hardware) calls) • Thin interface • Userspace kernel Guest Kernel app • Performance issues (e.g., Linux) Monitor Process (e.g., QEMU) Host Kernel with Host Kernel/Hypervisor namespacing (e.g., Linux/KVM) -
Efficient Cache Attacks on AES, and Countermeasures
J. Cryptol. (2010) 23: 37–71 DOI: 10.1007/s00145-009-9049-y Efficient Cache Attacks on AES, and Countermeasures Eran Tromer Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 32 Vassar Street, G682, Cambridge, MA 02139, USA [email protected] and Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100, Israel Dag Arne Osvik Laboratory for Cryptologic Algorithms, Station 14, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland dagarne.osvik@epfl.ch Adi Shamir Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100, Israel [email protected] Communicated by Lars R. Knudsen Received 20 July 2007 and revised 25 June 2009 Online publication 23 July 2009 Abstract. We describe several software side-channel attacks based on inter-process leakage through the state of the CPU’s memory cache. This leakage reveals memory access patterns, which can be used for cryptanalysis of cryptographic primitives that employ data-dependent table lookups. The attacks allow an unprivileged process to attack other processes running in parallel on the same processor, despite partitioning methods such as memory protection, sandboxing, and virtualization. Some of our meth- ods require only the ability to trigger services that perform encryption or MAC using the unknown key, such as encrypted disk partitions or secure network links. Moreover, we demonstrate an extremely strong type of attack, which requires knowledge of nei- ther the specific plaintexts nor ciphertexts and works by merely monitoring the effect of the cryptographic process on the cache. We discuss in detail several attacks on AES and experimentally demonstrate their applicability to real systems, such as OpenSSL and Linux’s dm-crypt encrypted partitions (in the latter case, the full key was recov- ered after just 800 writes to the partition, taking 65 milliseconds). -
Jails and Unikernels
Virtualisation: Jails and Unikernels Advanced Operating Systems Lecture 18 Colin Perkins | https://csperkins.org/ | Copyright © 2017 | This work is licensed under the Creative Commons Attribution-NoDerivatives 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nd/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA. Lecture Outline • Alternatives to full virtualisation • Sandboxing processes: • FreeBSD jails and Linux containers • Container management • Unikernels and library operating systems Colin Perkins | https://csperkins.org/ | Copyright © 2017 2 Alternatives to Full Virtualisation • Full operating system virtualisation is expensive • Need to run a hypervisor • Need to run a complete guest operating system instance for each VM • High memory and storage overhead, high CPU load from running multiple OS instances on a single machine – but excellent isolation between VMs • Running multiple services on a single OS instance can offer insufficient isolation • All must share the same OS • A bug in a privileged service can easily compromise entire system – all services running on the host, and any unrelated data • A sandbox is desirable – to isolate multiple services running on a single operating system Colin Perkins | https://csperkins.org/ | Copyright © 2017 3 Sandboxing: Jails and Containers • Concept – lightweight virtualisation • A single operating system kernel • Multiple services /bin • Each service runs within a jail a service specific container, running just what’s needed /bin /dev for that application /dev /etc /etc /mail /home /home /jail /www /lib • Jail restricted to see only a subset of the / /lib /local /usr filesystem and processes of the host /usr /lib /sbin • A sandbox within the operating system /sbin /sbin /tmp /tmp /share /var • Partially virtualised /var Colin Perkins | https://csperkins.org/ | Copyright © 2017 4 Example: FreeBSD Jail subsystem Jails: Confining the omnipotent root. -
State Spill in Modern Operating Systems
A Characterization of State Spill in Modern Operating Systems Kevin Boos, Emilio Del Vecchio, and Lin Zhong Rice University fkevinaboos, edd5, [email protected] Abstract states change and propagate throughout the system, showing that modularity is necessary but insufficient. For example, Understanding and managing the propagation of states in several process migration works have cited “residual depen- operating systems has become an intractable problem due dencies” that remain on the source system as an obstacle to to their sheer size and complexity. Despite modularization post-migration correctness on the target system [38, 55, 34]. efforts, it remains a significant barrier to many contemporary Fault isolation and fault tolerance literature has long realized computing goals: process migration, fault isolation and the undesirable effects of fate sharing among software mod- tolerance, live update, software virtualization, and more. ules as well as the difficulty of restoring a process or whole Though many previous OS research endeavors have achieved machine statefully after a failure, due to the sprawl of states these goals through ad-hoc, tedious methods, we argue that spread among different system components [28, 26, 52, 51]. they have missed the underlying reason why these goals are Live update and hot-swapping research has long sought to overcome the state maintenance issues and inter-module de- so challenging: state spill. pendencies that plague their implementations when transi- State spill occurs when a software entity’s state undergoes tioning from an old to a new version, forcing developers to lasting changes as a result of a transaction from another entity. write complex state transfer functions [7, 25, 27, 48, 5]. -
In the Context of the CS3551 Spire Class Project
Unikernels: Library Operating Systems for the Cloud Anil Madhavapeddy, Richard Mortier, Charalampos Rotsos, David Scott, Balraj Singh, Thomas Gazagnaire, Steven Smith, Steven Hand and Jon Crowcroft ASPLOS’13 In The Context of the CS3551 Spire Class Project Brad Whitehead and Mike Boby February 25, 2020 Teaching Moment - What is a Unikernel? To answer that question, we have to take a look at the structure of a modern operating system Doesn’t matter if it’s Microsoft Windows, Linux, UNIX, Mac OS X OS X macOS, etc. All the mainstream operating systems have the same fundamental anatomy The Anatomy of an Operating System “The Kernel” Runs in Special Hardware Mode “Userland” – “Ring 0” Where Applications Run Only Program That Can Access or Allocate Resources No Privileges Copies Data Between Can Not Access Resources Programs Can Not “Talk” to Other Programs Growth of Operating Systems Linux Kernel is now 28 million lines of source code! Windows is estimated at 50 million lines of code!! With an industry average of 15-50 defects per 1000 lines of code*: Linux (Just the kernel) = 420 thousand to 1.4 million defects Windows = 750 thousand to 2.5 million defects * Steve McConnel, “Code Complete 2”, 2005 It Gets Worse The “Userland” support software is often 10 to 20 times larger than the kernel Red Hat Enterprise Linux (RHEL) Userland is approximately 420 million lines of code Try not to think about the 6.7 to 22 million defects running on the SCADA server controlling your power grid and drinking water Can It Get Even Worse? -
Rump File Systems Kernel Code Reborn
Rump File Systems Kernel Code Reborn Antti Kantee [email protected] Helsinki University of Technology USENIX Annual Technical Conference, San Diego, USA June 2009 Introduction ● kernel / userspace dichotomy – interfaces dictate environment ● make kernel file systems run in userspace in a complete and maintainable way – full stack, no code forks or #ifdef ● file system is a protocol translator – read(off,size,n) => blocks 001,476,711,999 Implementation status ● NetBSD kernel file system code runs unmodified in a userspace process ● total of 13 kernel file systems – cd9660, efs, ext2fs, fat, ffs, hfs+, lfs, nfs, ntfs, puffs, sysvbfs, tmpfs, udf – disk, memory, network, ”other” ● implementation shipped as source and binary with NetBSD 5.0 and later Terminology rump: runnable userspace meta program 1) userspace program using kernel code 2) framework which enables above rump kernel: part of rump with kernel code host (OS): system running the rump(1) Talk outline motivation use cases implementation evaluation Motivation ● original motivation: kernel development ● additional benefits: – security – code reuse in userspace tools – kernel code reuse on other systems Contrasts 1)usermode OS, emulator, virtual machine, second machine, turing machine, etc. – acknowledge that we already have an OS – vm simplifications, abstraction shortcuts, etc. – direct host service (no additional userland) 2)userspace file systems (e.g. FUSE) – reuse existing code, not write new code against another interface Talk outline motivation use cases implementation evaluation -
Library Operating Systems for the Cloud
Unikernels: Library Operating Systems for the Cloud Anil Madhavapeddy, Richard Mortier1, Charalampos Rotsos, David Scott2, Balraj Singh, Thomas Gazagnaire3, Steven Smith, Steven Hand and Jon Crowcroft University of Cambridge, University of Nottingham1, Citrix Systems Ltd2, OCamlPro SAS3 fi[email protected], fi[email protected], [email protected], fi[email protected] Abstract Configuration Files Mirage Compiler We present unikernels, a new approach to deploying cloud services application source code via applications written in high-level source code. Unikernels are Application Binary configuration files single-purpose appliances that are compile-time specialised into Language Runtime hardware architecture standalone kernels, and sealed against modification when deployed whole-system optimisation to a cloud platform. In return they offer significant reduction in Parallel Threads image sizes, improved efficiency and security, and should reduce operational costs. Our Mirage prototype compiles OCaml code into User Processes Application Code specialised unikernels that run on commodity clouds and offer an order of unikernel magnitude reduction in code size without significant performance OS Kernel Mirage Runtime } penalty. The architecture combines static type-safety with a single address-space layout that can be made immutable via a hypervisor Hypervisor Hypervisor extension. Mirage contributes a suite of type-safe protocol libraries, and our results demonstrate that the hypervisor is a platform that Hardware Hardware overcomes the hardware compatibility issues that have made past library operating systems impractical to deploy in the real-world. Figure 1: Contrasting software layers in existing VM appliances vs. Categories and Subject Descriptors D.4 [Operating Systems]: unikernel’s standalone kernel compilation approach. -
A Survey of Microarchitectural Timing Attacks and Countermeasures on Contemporary Hardware
A Survey of Microarchitectural Timing Attacks and Countermeasures on Contemporary Hardware Qian Ge1, Yuval Yarom2, David Cock1,3, and Gernot Heiser1 1Data61, CSIRO and UNSW, Australia, qian.ge, [email protected] 2Data61, CSIRO and the University of Adelaide, Australia, [email protected] 3Present address: Systems Group, Department of Computer Science, ETH Zurich,¨ [email protected] Abstract Microarchitectural timing channels expose hidden hardware state though timing. We survey recent attacks that exploit microarchitectural features in shared hardware, especially as they are relevant for cloud computing. We classify types of attacks according to a taxonomy of the shared resources leveraged for such attacks. Moreover, we take a detailed look at attacks used against shared caches. We survey existing countermeasures. We finally discuss trends in the attacks, challenges to combating them, and future directions, especially with respect to hardware support. 1 Introduction Computers are increasingly handling sensitive data (banking, voting), while at the same time we consolidate more services, sensitive or not, on a single hardware platform. This trend is driven both by cost savings and convenience. The most visible example is the cloud computing—infrastructure-as-a-service (IaaS) cloud computing supports multiple virtual machines (VM) on a hardware platform managed by a virtual machine monitor (VMM) or hypervisor. These co-resident VMs are mutually distrusting: high-performance computing software may run alongside a data centre for financial markets, requiring the platform to ensure confidentiality and integrity of VMs. The cloud computing platform also has availability requirements: service providers have service-level agreements (SLAs) which specify availability targets, and malicious VMs being able to deny service to a co-resident VM could be costly to the service provider.