Fuzzing with Code Fragments
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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 -
BUGS in the SYSTEM a Primer on the Software Vulnerability Ecosystem and Its Policy Implications
ANDI WILSON, ROSS SCHULMAN, KEVIN BANKSTON, AND TREY HERR BUGS IN THE SYSTEM A Primer on the Software Vulnerability Ecosystem and its Policy Implications JULY 2016 About the Authors About New America New America is committed to renewing American politics, Andi Wilson is a policy analyst at New America’s Open prosperity, and purpose in the Digital Age. We generate big Technology Institute, where she researches and writes ideas, bridge the gap between technology and policy, and about the relationship between technology and policy. curate broad public conversation. We combine the best of With a specific focus on cybersecurity, Andi is currently a policy research institute, technology laboratory, public working on issues including encryption, vulnerabilities forum, media platform, and a venture capital fund for equities, surveillance, and internet freedom. ideas. We are a distinctive community of thinkers, writers, researchers, technologists, and community activists who Ross Schulman is a co-director of the Cybersecurity believe deeply in the possibility of American renewal. Initiative and senior policy counsel at New America’s Open Find out more at newamerica.org/our-story. Technology Institute, where he focuses on cybersecurity, encryption, surveillance, and Internet governance. Prior to joining OTI, Ross worked for Google in Mountain About the Cybersecurity Initiative View, California. Ross has also worked at the Computer The Internet has connected us. Yet the policies and and Communications Industry Association, the Center debates that surround the security of our networks are for Democracy and Technology, and on Capitol Hill for too often disconnected, disjointed, and stuck in an Senators Wyden and Feingold. unsuccessful status quo. -
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. -
How to Analyze the Cyber Threat from Drones
C O R P O R A T I O N KATHARINA LEY BEST, JON SCHMID, SHANE TIERNEY, JALAL AWAN, NAHOM M. BEYENE, MAYNARD A. HOLLIDAY, RAZA KHAN, KAREN LEE How to Analyze the Cyber Threat from Drones Background, Analysis Frameworks, and Analysis Tools For more information on this publication, visit www.rand.org/t/RR2972 Library of Congress Cataloging-in-Publication Data is available for this publication. ISBN: 978-1-9774-0287-5 Published by the RAND Corporation, Santa Monica, Calif. © Copyright 2020 RAND Corporation R® is a registered trademark. Cover design by Rick Penn-Kraus Cover images: drone, Kadmy - stock.adobe.com; data, Getty Images. Limited Print and Electronic Distribution Rights This document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited. Permission is given to duplicate this document for personal use only, as long as it is unaltered and complete. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial use. For information on reprint and linking permissions, please visit www.rand.org/pubs/permissions. The RAND Corporation is a research organization that develops solutions to public policy challenges to help make communities throughout the world safer and more secure, healthier and more prosperous. RAND is nonprofit, nonpartisan, and committed to the public interest. RAND’s publications do not necessarily reflect the opinions of its research clients and sponsors. Support RAND Make a tax-deductible charitable contribution at www.rand.org/giving/contribute www.rand.org Preface This report explores the security implications of the rapid growth in unmanned aerial systems (UAS), focusing specifically on current and future vulnerabilities. -
The CLASP Application Security Process
The CLASP Application Security Process Secure Software, Inc. Copyright (c) 2005, Secure Software, Inc. The CLASP Application Security Process The CLASP Application Security Process TABLE OF CONTENTS CHAPTER 1 Introduction 1 CLASP Status 4 An Activity-Centric Approach 4 The CLASP Implementation Guide 5 The Root-Cause Database 6 Supporting Material 7 CHAPTER 2 Implementation Guide 9 The CLASP Activities 11 Institute security awareness program 11 Monitor security metrics 12 Specify operational environment 13 Identify global security policy 14 Identify resources and trust boundaries 15 Identify user roles and resource capabilities 16 Document security-relevant requirements 17 Detail misuse cases 18 Identify attack surface 19 Apply security principles to design 20 Research and assess security posture of technology solutions 21 Annotate class designs with security properties 22 Specify database security configuration 23 Perform security analysis of system requirements and design (threat modeling) 24 Integrate security analysis into source management process 25 Implement interface contracts 26 Implement and elaborate resource policies and security technologies 27 Address reported security issues 28 Perform source-level security review 29 Identify, implement and perform security tests 30 The CLASP Application Security Process i Verify security attributes of resources 31 Perform code signing 32 Build operational security guide 33 Manage security issue disclosure process 34 Developing a Process Engineering Plan 35 Business objectives 35 Process -
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. -
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. -
Threats and Vulnerabilities in Federation Protocols and Products
Threats and Vulnerabilities in Federation Protocols and Products Teemu Kääriäinen, CSSLP / Nixu Corporation OWASP Helsinki Chapter Meeting #30 October 11, 2016 Contents • Federation Protocols: OpenID Connect and SAML 2.0 – Basic flows, comparison between the protocols • OAuth 2.0 and OpenID Connect Vulnerabilities and Best Practices – Background for OAuth 2.0 security criticism, vulnerabilities related discussion and publicly disclosed vulnerabilities, best practices, JWT, authorization bypass vulnerabilities, mobile application integration. • SAML 2.0 Vulnerabilities and Best Practices – Best practices, publicly disclosed vulnerabilities • OWASP Top Ten in Access management solutions – Focus on Java deserialization vulnerabilites in different commercial and open source access management products • Forgerock OpenAM, Gluu, CAS, PingFederate 7.3.0 Admin UI, Oracle ADF (Oracle Identity Manager) Federation Protocols: OpenID Connect and SAML 2.0 • OpenID Connect is an emerging technology built on OAuth 2.0 that enables relying parties to verify the identity of an end-user in an interoperable and REST-like manner. • OpenID Connect is not just about authentication. It is also about authorization, delegation and API access management. • Reasons for services to start using OpenID Connect: – Ease of integration. – Ability to integrate client applications running on different platforms: single-page app, web, backend, mobile, IoT. – Allowing 3rd party integrations in a secure, interoperable and scalable manner. • OpenID Connect is proven to be secure and mature technology: – Solves many of the security issues that have been an issue with OAuth 2.0. • OpenID Connect and OAuth 2.0 are used frequently in social login scenarios: – E.g. Google and Microsoft Account are OpenID Connect Identity Providers. Facebook is an OAuth 2.0 authorization server. -
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. -
Seed Selection for Successful Fuzzing
Seed Selection for Successful Fuzzing Adrian Herrera Hendra Gunadi Shane Magrath ANU & DST ANU DST Australia Australia Australia Michael Norrish Mathias Payer Antony L. Hosking CSIRO’s Data61 & ANU EPFL ANU & CSIRO’s Data61 Australia Switzerland Australia ABSTRACT ACM Reference Format: Mutation-based greybox fuzzing—unquestionably the most widely- Adrian Herrera, Hendra Gunadi, Shane Magrath, Michael Norrish, Mathias Payer, and Antony L. Hosking. 2021. Seed Selection for Successful Fuzzing. used fuzzing technique—relies on a set of non-crashing seed inputs In Proceedings of the 30th ACM SIGSOFT International Symposium on Software (a corpus) to bootstrap the bug-finding process. When evaluating a Testing and Analysis (ISSTA ’21), July 11–17, 2021, Virtual, Denmark. ACM, fuzzer, common approaches for constructing this corpus include: New York, NY, USA, 14 pages. https://doi.org/10.1145/3460319.3464795 (i) using an empty file; (ii) using a single seed representative of the target’s input format; or (iii) collecting a large number of seeds (e.g., 1 INTRODUCTION by crawling the Internet). Little thought is given to how this seed Fuzzing is a dynamic analysis technique for finding bugs and vul- choice affects the fuzzing process, and there is no consensus on nerabilities in software, triggering crashes in a target program by which approach is best (or even if a best approach exists). subjecting it to a large number of (possibly malformed) inputs. To address this gap in knowledge, we systematically investigate Mutation-based fuzzing typically uses an initial set of valid seed and evaluate how seed selection affects a fuzzer’s ability to find bugs inputs from which to generate new seeds by random mutation. -
Manipulating I/Os and Repurposing Binary Code to Enable Instrumented Fuzzing in ICS Control Applications
ICSFuzz: Manipulating I/Os and Repurposing Binary Code to Enable Instrumented Fuzzing in ICS Control Applications Dimitrios Tychalas1, Hadjer Benkraouda2 and Michail Maniatakos2 1NYU Tandon School of Engineering, Brooklyn, NY, USA 2New York University Abu Dhabi, Abu Dhabi, UAE Abstract critical infrastructures such as power grids, oil and gas indus- tries, transportation and water treatment facilities. Possible Industrial Control Systems (ICS) have seen a rapid prolif- suspension of their operation may cause severe complications eration in the last decade amplified by the advent of the 4th which translate to significant loss of revenue, environmental Industrial Revolution. At the same time, several notable cyber- disasters or even human casualties [22, 47]. security incidents in industrial environments have underlined Since safety and security are tightly correlated in ICS en- the lack of depth in security evaluation of industrial devices vironments, the recent cyberattacks that targeted industrial such as Programmable Logic Controllers (PLC). Modern settings have showcased tangible threats to contemporary in- PLCs are based on widely used microprocessors and deploy dustrial environments. The most prominent of these incidents, commodity operating systems (e.g., ARM on Linux). Thus, Stuxnet [30], drew widespread attention when discovered, threats from the information technology domain can be read- as the first potential case of cyberwarfare. In the following ily ported to industrial environments. PLC application bi- years more incidents including the 2015/2016 cyberattacks naries in particular have never been considered as regular on the Ukrainian power grid [33, 62] and the 2017 attack programs able to introduce traditional security threats, such on petrochemical facilities in Saudi Arabia [42] have helped as buffer overflows.