Fuzzing File Systems Via Two-Dimensional Input Space Exploration
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Elastic Storage for Linux on System Z IBM Research & Development Germany
Peter Münch T/L Test and Development – Elastic Storage for Linux on System z IBM Research & Development Germany Elastic Storage for Linux on IBM System z © Copyright IBM Corporation 2014 9.0 Elastic Storage for Linux on System z Session objectives • This presentation introduces the Elastic Storage, based on General Parallel File System technology that will be available for Linux on IBM System z. Understand the concepts of Elastic Storage and which functions will be available for Linux on System z. Learn how you can integrate and benefit from the Elastic Storage in a Linux on System z environment. Finally, get your first impression in a live demo of Elastic Storage. 2 © Copyright IBM Corporation 2014 Elastic Storage for Linux on System z Trademarks The following are trademarks of the International Business Machines Corporation in the United States and/or other countries. AIX* FlashSystem Storwize* Tivoli* DB2* IBM* System p* WebSphere* DS8000* IBM (logo)* System x* XIV* ECKD MQSeries* System z* z/VM* * Registered trademarks of IBM Corporation The following are trademarks or registered trademarks of other companies. Adobe, the Adobe logo, PostScript, and the PostScript logo are either registered trademarks or trademarks of Adobe Systems Incorporated in the United States, and/or other countries. Cell Broadband Engine is a trademark of Sony Computer Entertainment, Inc. in the United States, other countries, or both and is used under license therefrom. Intel, Intel logo, Intel Inside, Intel Inside logo, Intel Centrino, Intel Centrino logo, Celeron, Intel Xeon, Intel SpeedStep, Itanium, and Pentium are trademarks or registered trademarks of Intel Corporation or its subsidiaries in the United States and other countries. -
Automatically Bypassing Android Malware Detection System
FUZZIFICATION: Anti-Fuzzing Techniques Jinho Jung, Hong Hu, David Solodukhin, Daniel Pagan, Kyu Hyung Lee*, Taesoo Kim * 1 Fuzzing Discovers Many Vulnerabilities 2 Fuzzing Discovers Many Vulnerabilities 3 Testers Find Bugs with Fuzzing Detected bugs Normal users Compilation Source Released binary Testers Compilation Distribution Fuzzing 4 But Attackers Also Find Bugs Detected bugs Normal users Compilation Attackers Source Released binary Testers Compilation Distribution Fuzzing 5 Our work: Make the Fuzzing Only Effective to the Testers Detected bugs Normal users Fuzzification ? Fortified binary Attackers Source Compilation Binary Testers Compilation Distribution Fuzzing 6 Threat Model Detected bugs Normal users Fuzzification Fortified binary Attackers Source Compilation Binary Testers Compilation Distribution Fuzzing 7 Threat Model Detected bugs Normal users Fuzzification Fortified binary Attackers Source Compilation Binary Testers Compilation Distribution Fuzzing Adversaries try to find vulnerabilities from fuzzing 8 Threat Model Detected bugs Normal users Fuzzification Fortified binary Attackers Source Compilation Binary Testers Compilation Distribution Fuzzing Adversaries only have a copy of fortified binary 9 Threat Model Detected bugs Normal users Fuzzification Fortified binary Attackers Source Compilation Binary Testers Compilation Distribution Fuzzing Adversaries know Fuzzification and try to nullify 10 Research Goals Detected bugs Normal users Fuzzification Fortified binary Attackers Source Compilation Binary Testers Compilation -
Membrane: Operating System Support for Restartable File Systems Swaminathan Sundararaman, Sriram Subramanian, Abhishek Rajimwale, Andrea C
Membrane: Operating System Support for Restartable File Systems Swaminathan Sundararaman, Sriram Subramanian, Abhishek Rajimwale, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau, Michael M. Swift Computer Sciences Department, University of Wisconsin, Madison Abstract and most complex code bases in the kernel. Further, We introduce Membrane, a set of changes to the oper- file systems are still under active development, and new ating system to support restartable file systems. Mem- ones are introduced quite frequently. For example, Linux brane allows an operating system to tolerate a broad has many established file systems, including ext2 [34], class of file system failures and does so while remain- ext3 [35], reiserfs [27], and still there is great interest in ing transparent to running applications; upon failure, the next-generation file systems such as Linux ext4 and btrfs. file system restarts, its state is restored, and pending ap- Thus, file systems are large, complex, and under develop- plication requests are serviced as if no failure had oc- ment, the perfect storm for numerous bugs to arise. curred. Membrane provides transparent recovery through Because of the likely presence of flaws in their imple- a lightweight logging and checkpoint infrastructure, and mentation, it is critical to consider how to recover from includes novel techniques to improve performance and file system crashes as well. Unfortunately, we cannot di- correctness of its fault-anticipation and recovery machin- rectly apply previous work from the device-driver litera- ery. We tested Membrane with ext2, ext3, and VFAT. ture to improving file-system fault recovery. File systems, Through experimentation, we show that Membrane in- unlike device drivers, are extremely stateful, as they man- duces little performance overhead and can tolerate a wide age vast amounts of both in-memory and persistent data; range of file system crashes. -
Developments in GFS2
Developments in GFS2 Andy Price <[email protected]> Software Engineer, GFS2 OSSEU 2018 11 GFS2 recap ● Shared storage cluster filesystem ● High availability clusters ● Uses glocks (“gee-locks”) based on DLM locking ● One journal per node ● Divided into resource groups ● Requires clustered lvm: clvmd/lvmlockd ● Userspace tools: gfs2-utils 22 Not-so-recent developments ● Full SELinux support (linux 4.5) ● Previously no way to tell other nodes that cached labels are invalid ● Workaround was to mount with -o context=<label> ● Relabeling now causes security label invalidation across cluster 33 Not-so-recent developments ● Resource group stripe alignment (gfs2-utils 3.1.11) ● mkfs.gfs2 tries to align resource groups to RAID stripes where possible ● Uses libblkid topology information to find stripe unit and stripe width values ● Tries to spread resource groups evenly across disks 44 Not-so-recent developments ● Resource group LVBs (linux 3.6) ● -o rgrplvb (all nodes) ● LVBs: data attached to DLM lock requests ● Allows resource group metadata to be cached and transferred with glocks ● Decreases resource group-related I/O 55 Not-so-recent developments ● Location-based readdir cookies (linux 4.5) ● -o loccookie (all nodes) ● Uniqueness required by NFS ● Previously 31 bits of filename hash ● Problem: collisions with large directories (100K+ files) ● Cookies now based on the location of the directory entry within the directory 66 Not-so-recent developments ● gfs_controld is gone (linux 3.3) ● dlm now triggers gfs2 journal recovery via callbacks ● -
Globalfs: a Strongly Consistent Multi-Site File System
GlobalFS: A Strongly Consistent Multi-Site File System Leandro Pacheco Raluca Halalai Valerio Schiavoni University of Lugano University of Neuchatelˆ University of Neuchatelˆ Fernando Pedone Etienne Riviere` Pascal Felber University of Lugano University of Neuchatelˆ University of Neuchatelˆ Abstract consistency, availability, and tolerance to partitions. Our goal is to ensure strongly consistent file system operations This paper introduces GlobalFS, a POSIX-compliant despite node failures, at the price of possibly reduced geographically distributed file system. GlobalFS builds availability in the event of a network partition. Weak on two fundamental building blocks, an atomic multicast consistency is suitable for domain-specific applications group communication abstraction and multiple instances of where programmers can anticipate and provide resolution a single-site data store. We define four execution modes and methods for conflicts, or work with last-writer-wins show how all file system operations can be implemented resolution methods. Our rationale is that for general-purpose with these modes while ensuring strong consistency and services such as a file system, strong consistency is more tolerating failures. We describe the GlobalFS prototype in appropriate as it is both more intuitive for the users and detail and report on an extensive performance assessment. does not require human intervention in case of conflicts. We have deployed GlobalFS across all EC2 regions and Strong consistency requires ordering commands across show that the system scales geographically, providing replicas, which needs coordination among nodes at performance comparable to other state-of-the-art distributed geographically distributed sites (i.e., regions). Designing file systems for local commands and allowing for strongly strongly consistent distributed systems that provide good consistent operations over the whole system. -
Add-Ons for Red Hat Enterprise Linux
DATASHEET ADD-ONS FOR RED HAT ENTERPRISE LINUX WORKLOAD AND MISSION-CRITICAL PLATFORM ENHANCEMENTS In conjunction with Red Hat® Enterprise Linux®, Red Hat offers a portfolio of Add-Ons to extend the features of your Red Hat Enterprise Linux subscription. Add-Ons to Red Hat Enterprise Linux tailor your application environment to suit your particular computing requirements. With increased flexibility and choice, customers can deploy what they need, when they need it. ADD-ON OPTIONS FOR AVAILABILITY MANAGEMENT High Availability Add-On Red Hat’s High Availability Add-On provides on-demand failover services between nodes within a cluster, making applications highly available. The High Availability Add-On supports up to 16 nodes and may be configured for most applications that use customizable agents, as well as for virtual guests. The High Availability Add-On also includes failover support for off-the-shelf applications like Apache, MySQL, and PostgreSQL. When using the High Availability Add-On, a highly available service can fail over from one node to another with no apparent interruption to cluster clients. The High Availability Add-On also ensures data integrity when one cluster node takes over control of a service from another clus- ter node. It achieves this by promptly evicting nodes from the cluster that are deemed to be faulty using a method called “fencing” that prevents data corruption. www.redhat.com DATASHEET ADD-ONS For RED Hat ENterprise LINUX 6 Resilient Storage Add-On Red Hat’s Resilient Storage Add-On enables a shared storage or clustered file system to access the same storage device over a network. -
Moonshine: Optimizing OS Fuzzer Seed Selection with Trace Distillation
MoonShine: Optimizing OS Fuzzer Seed Selection with Trace Distillation Shankara Pailoor, Andrew Aday, and Suman Jana Columbia University Abstract bug in system call implementations might allow an un- privileged user-level process to completely compromise OS fuzzers primarily test the system-call interface be- the system. tween the OS kernel and user-level applications for secu- OS fuzzers usually start with a set of synthetic seed rity vulnerabilities. The effectiveness of all existing evo- programs , i.e., a sequence of system calls, and itera- lutionary OS fuzzers depends heavily on the quality and tively mutate their arguments/orderings using evolution- diversity of their seed system call sequences. However, ary guidance to maximize the achieved code coverage. generating good seeds for OS fuzzing is a hard problem It is well-known that the performance of evolutionary as the behavior of each system call depends heavily on fuzzers depend critically on the quality and diversity of the OS kernel state created by the previously executed their seeds [31, 39]. Ideally, the synthetic seed programs system calls. Therefore, popular evolutionary OS fuzzers for OS fuzzers should each contain a small number of often rely on hand-coded rules for generating valid seed system calls that exercise diverse functionality in the OS sequences of system calls that can bootstrap the fuzzing kernel. process. Unfortunately, this approach severely restricts However, the behavior of each system call heavily de- the diversity of the seed system call sequences and there- pends on the shared kernel state created by the previous fore limits the effectiveness of the fuzzers. -
Active Fuzzing for Testing and Securing Cyber-Physical Systems
Active Fuzzing for Testing and Securing Cyber-Physical Systems Yuqi Chen Bohan Xuan Christopher M. Poskitt Singapore Management University Zhejiang University Singapore Management University Singapore China Singapore [email protected] [email protected] [email protected] Jun Sun Fan Zhang∗ Singapore Management University Zhejiang University Singapore China [email protected] [email protected] ABSTRACT KEYWORDS Cyber-physical systems (CPSs) in critical infrastructure face a per- Cyber-physical systems; fuzzing; active learning; benchmark gen- vasive threat from attackers, motivating research into a variety of eration; testing defence mechanisms countermeasures for securing them. Assessing the effectiveness of ACM Reference Format: these countermeasures is challenging, however, as realistic bench- Yuqi Chen, Bohan Xuan, Christopher M. Poskitt, Jun Sun, and Fan Zhang. marks of attacks are difficult to manually construct, blindly testing 2020. Active Fuzzing for Testing and Securing Cyber-Physical Systems. In is ineffective due to the enormous search spaces and resource re- Proceedings of the 29th ACM SIGSOFT International Symposium on Software quirements, and intelligent fuzzing approaches require impractical Testing and Analysis (ISSTA ’20), July 18–22, 2020, Virtual Event, USA. ACM, amounts of data and network access. In this work, we propose active New York, NY, USA, 13 pages. https://doi.org/10.1145/3395363.3397376 fuzzing, an automatic approach for finding test suites of packet- level CPS network attacks, targeting scenarios in which attackers 1 INTRODUCTION can observe sensors and manipulate packets, but have no existing knowledge about the payload encodings. Our approach learns re- Cyber-physical systems (CPSs), characterised by their tight and gression models for predicting sensor values that will result from complex integration of computational and physical processes, are sampled network packets, and uses these predictions to guide a often used in the automation of critical public infrastructure [78]. -
The Art, Science, and Engineering of Fuzzing: a Survey
1 The Art, Science, and Engineering of Fuzzing: A Survey Valentin J.M. Manes,` HyungSeok Han, Choongwoo Han, Sang Kil Cha, Manuel Egele, Edward J. Schwartz, and Maverick Woo Abstract—Among the many software vulnerability discovery techniques available today, fuzzing has remained highly popular due to its conceptual simplicity, its low barrier to deployment, and its vast amount of empirical evidence in discovering real-world software vulnerabilities. At a high level, fuzzing refers to a process of repeatedly running a program with generated inputs that may be syntactically or semantically malformed. While researchers and practitioners alike have invested a large and diverse effort towards improving fuzzing in recent years, this surge of work has also made it difficult to gain a comprehensive and coherent view of fuzzing. To help preserve and bring coherence to the vast literature of fuzzing, this paper presents a unified, general-purpose model of fuzzing together with a taxonomy of the current fuzzing literature. We methodically explore the design decisions at every stage of our model fuzzer by surveying the related literature and innovations in the art, science, and engineering that make modern-day fuzzers effective. Index Terms—software security, automated software testing, fuzzing. ✦ 1 INTRODUCTION Figure 1 on p. 5) and an increasing number of fuzzing Ever since its introduction in the early 1990s [152], fuzzing studies appear at major security conferences (e.g. [225], has remained one of the most widely-deployed techniques [52], [37], [176], [83], [239]). In addition, the blogosphere is to discover software security vulnerabilities. At a high level, filled with many success stories of fuzzing, some of which fuzzing refers to a process of repeatedly running a program also contain what we consider to be gems that warrant a with generated inputs that may be syntactically or seman- permanent place in the literature. -
Veritas Access Administrator's Guide
Veritas Access Administrator's Guide 7.4.2 Linux To be used with the Veritas Access Appliance v7.4.2 (3340) documentation April 2021 Veritas Access Administrator's Guide Last updated: 2021-04-15 Document version: 7.4.2 Rev 5 Legal Notice Copyright © 2018 Veritas Technologies LLC. All rights reserved. Veritas, the Veritas Logo, Veritas InfoScale, and NetBackup are trademarks or registered trademarks of Veritas Technologies LLC or its affiliates in the U.S. and other countries. Other names may be trademarks of their respective owners. This product may contain third-party software for which Veritas is required to provide attribution to the third party (“Third-Party Programs”). Some of the Third-Party Programs are available under open source or free software licenses. The License Agreement accompanying the Software does not alter any rights or obligations you may have under those open source or free software licenses. Refer to the third-party legal notices document accompanying this Veritas product or available at: https://www.veritas.com/licensing/process The product described in this document is distributed under licenses restricting its use, copying, distribution, and decompilation/reverse engineering. No part of this document may be reproduced in any form by any means without prior written authorization of Veritas Technologies LLC and its licensors, if any. THE DOCUMENTATION IS PROVIDED "AS IS" AND ALL EXPRESS OR IMPLIED CONDITIONS, REPRESENTATIONS AND WARRANTIES, INCLUDING ANY IMPLIED WARRANTY OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE OR NON-INFRINGEMENT, ARE DISCLAIMED, EXCEPT TO THE EXTENT THAT SUCH DISCLAIMERS ARE HELD TO BE LEGALLY INVALID. VERITAS TECHNOLOGIES LLC SHALL NOT BE LIABLE FOR INCIDENTAL OR CONSEQUENTIAL DAMAGES IN CONNECTION WITH THE FURNISHING, PERFORMANCE, OR USE OF THIS DOCUMENTATION. -
Psofuzzer: a Target-Oriented Software Vulnerability Detection Technology Based on Particle Swarm Optimization
applied sciences Article PSOFuzzer: A Target-Oriented Software Vulnerability Detection Technology Based on Particle Swarm Optimization Chen Chen 1,2,*, Han Xu 1 and Baojiang Cui 1 1 School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing 100876, China; [email protected] (H.X.); [email protected] (B.C.) 2 School of Information and Navigation, Air Force Engineering University, Xi’an 710077, China * Correspondence: [email protected] Abstract: Coverage-oriented and target-oriented fuzzing are widely used in vulnerability detection. Compared with coverage-oriented fuzzing, target-oriented fuzzing concentrates more computing resources on suspected vulnerable points to improve the testing efficiency. However, the sample generation algorithm used in target-oriented vulnerability detection technology has some problems, such as weak guidance, weak sample penetration, and difficult sample generation. This paper proposes a new target-oriented fuzzer, PSOFuzzer, that uses particle swarm optimization to generate samples. PSOFuzzer can quickly learn high-quality features in historical samples and implant them into new samples that can be led to execute the suspected vulnerable point. The experimental results show that PSOFuzzer can generate more samples in the test process to reach the target point and can trigger vulnerabilities with 79% and 423% higher probability than AFLGo and Sidewinder, respectively, on tested software programs. Keywords: fuzzing; model-based fuzzing; vulnerability detection; code coverage; open-source program; directed fuzzing; static instrumentation; source code instrumentation Citation: Chen, C.; Han, X.; Cui, B. PSOFuzzer: A Target-Oriented 1. Introduction Software Vulnerability Detection The appearance of an increasing number of software vulnerabilities has made auto- Technology Based on Particle Swarm matic vulnerability detection technology a widespread concern in industry and academia. -
Configuration Fuzzing Testing Framework for Software Vulnerability Detection
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Columbia University Academic Commons CONFU: Configuration Fuzzing Testing Framework for Software Vulnerability Detection Huning Dai, Christian Murphy, Gail Kaiser Department of Computer Science Columbia University New York, NY 10027 USA ABSTRACT Many software security vulnerabilities only reveal themselves under certain conditions, i.e., particular configurations and inputs together with a certain runtime environment. One approach to detecting these vulnerabilities is fuzz testing. However, typical fuzz testing makes no guarantees regarding the syntactic and semantic validity of the input, or of how much of the input space will be explored. To address these problems, we present a new testing methodology called Configuration Fuzzing. Configuration Fuzzing is a technique whereby the configuration of the running application is mutated at certain execution points, in order to check for vulnerabilities that only arise in certain conditions. As the application runs in the deployment environment, this testing technique continuously fuzzes the configuration and checks "security invariants'' that, if violated, indicate a vulnerability. We discuss the approach and introduce a prototype framework called ConFu (CONfiguration FUzzing testing framework) for implementation. We also present the results of case studies that demonstrate the approach's feasibility and evaluate its performance. Keywords: Vulnerability; Configuration Fuzzing; Fuzz testing; In Vivo testing; Security invariants INTRODUCTION As the Internet has grown in popularity, security testing is undoubtedly becoming a crucial part of the development process for commercial software, especially for server applications. However, it is impossible in terms of time and cost to test all configurations or to simulate all system environments before releasing the software into the field, not to mention the fact that software distributors may later add more configuration options.