Fuzz Testing
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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 -
Opentext Product Security Assurance Program
The Information Company ™ Product Security Assurance Program Contents Objective 03 Scope 03 Sources 03 Introduction 03 Concept and design 04 Development 05 Testing and quality assurance 07 Maintain and support 09 Partnership and responsibility 10 Privavy and Security Policy 11 Product Security Assurance Program 2/11 Objective The goals of the OpenText Product Security Assurance Program (PSAP) are to help ensure that all products, solutions, and services are designed, developed, and maintained with security in mind, and to provide OpenText customers with the assurance that their important assets and information are protected at all times. This document provides a general, public overview of the key aspects and components of the PSAP program. Scope The scope of the PSAP includes all software solutions designed and developed by OpenText and its subsidiaries. All OpenText employees are responsible to uphold and participate in this program. Sources The source of this overview document is the PSAP Standard Operating Procedure (SOP). This SOP is highly confidential in nature, for internal OpenText consumption only. This overview document represents the aspects that are able to be shared with OpenText customers and partners. Introduction OpenText is committed to the confidentiality, integrity, and availability of its customer information. OpenText believes that the foundation of a highly secure system is that the security is built in to the software from the initial stages of its concept, design, development, deployment, and beyond. In this respect, -
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. -
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. -
Fuzzing with Code Fragments
Fuzzing with Code Fragments Christian Holler Kim Herzig Andreas Zeller Mozilla Corporation∗ Saarland University Saarland University [email protected] [email protected] [email protected] Abstract JavaScript interpreter must follow the syntactic rules of JavaScript. Otherwise, the JavaScript interpreter will re- Fuzz testing is an automated technique providing random ject the input as invalid, and effectively restrict the test- data as input to a software system in the hope to expose ing to its lexical and syntactic analysis, never reaching a vulnerability. In order to be effective, the fuzzed input areas like code transformation, in-time compilation, or must be common enough to pass elementary consistency actual execution. To address this issue, fuzzing frame- checks; a JavaScript interpreter, for instance, would only works include strategies to model the structure of the de- accept a semantically valid program. On the other hand, sired input data; for fuzz testing a JavaScript interpreter, the fuzzed input must be uncommon enough to trigger this would require a built-in JavaScript grammar. exceptional behavior, such as a crash of the interpreter. Surprisingly, the number of fuzzing frameworks that The LangFuzz approach resolves this conflict by using generate test inputs on grammar basis is very limited [7, a grammar to randomly generate valid programs; the 17, 22]. For JavaScript, jsfunfuzz [17] is amongst the code fragments, however, partially stem from programs most popular fuzzing tools, having discovered more that known to have caused invalid behavior before. LangFuzz 1,000 defects in the Mozilla JavaScript engine. jsfunfuzz is an effective tool for security testing: Applied on the is effective because it is hardcoded to target a specific Mozilla JavaScript interpreter, it discovered a total of interpreter making use of specific knowledge about past 105 new severe vulnerabilities within three months of and common vulnerabilities. -
Software Testing: Essential Phase of SDLC and a Comparative Study Of
International Journal of System and Software Engineering Volume 5 Issue 2, December 2017 ISSN.: 2321-6107 Software Testing: Essential Phase of SDLC and a Comparative Study of Software Testing Techniques Sushma Malik Assistant Professor, Institute of Innovation in Technology and Management, Janak Puri, New Delhi, India. Email: [email protected] Abstract: Software Development Life-Cycle (SDLC) follows In the software development process, the problem (Software) the different activities that are used in the development of a can be dividing in the following activities [3]: software product. SDLC is also called the software process ∑ Understanding the problem and it is the lifeline of any Software Development Model. ∑ Decide a plan for the solution Software Processes decide the survival of a particular software development model in the market as well as in ∑ Coding for the designed solution software organization and Software testing is a process of ∑ Testing the definite program finding software bugs while executing a program so that we get the zero defect software. The main objective of software These activities may be very complex for large systems. So, testing is to evaluating the competence and usability of a each of the activity has to be broken into smaller sub-activities software. Software testing is an important part of the SDLC or steps. These steps are then handled effectively to produce a because through software testing getting the quality of the software project or system. The basic steps involved in software software. Lots of advancements have been done through project development are: various verification techniques, but still we need software to 1) Requirement Analysis and Specification: The goal of be fully tested before handed to the customer. -
Secure by Design, Secure by Default: Requirements and Guidance
Biometrics and Surveillance Camera Commissioner Secure by Design, Secure by Default Video Surveillance Products Introduction This guidance is for any organisation manufacturing Video Surveillance Systems (VSS), or manufacturing or assembling components intended to be utilised as part of a VSS. It is intended to layout the Biometrics and Surveillance Camera Commissioners (BSCC) minimum requirements to ensure such systems are designed and manufactured in a manner that assures they are Secure by Design. It also contains certain component requirements that will ensure a configuration that is Secure by Default when the component is shipped, thereby making it more likely that the system will be installed and left in a secure state. This guidance forms part of a wider suite of documentation being developed as part of the SCC Strategy, in support of the SCC Code of Practice. Background and Context The nature of the Internet means that connected devices can be subjected to a cyber attack from anywhere in the world. Widespread attacks on connected products is a current and real threat, and a number of highly publicised attacks have already occurred. The Mirai malware targeted devices such as internet-enabled cameras (IP cameras). Mirai was successful because it exploited the use of common default credentials (such as a username and password being set by the manufacturer as ‘admin’) and poor security configuration of devices. Ultimately, this facilitated attacks on a range of commercial and social media services and included an outage of streaming services such as Netflix. An evolution of Mirai, called Reaper, has also been discovered. Reaper used publicly and easily available exploits that remained unfixed (patched) and highlighted the problem around non patching of known security vulnerabilities, allowing attackers to utilise them to cause harm. -
Stress Testing Embedded Software Applications
Embedded Systems Conference / Boston, MA September 20, 2007 ESC-302 Stress Testing Embedded Software Applications T. Adrian Hill Johns Hopkins University Applied Physics Laboratory [email protected] ABSTRACT This paper describes techniques to design stress tests, classifies the types of problems found during these types of tests, and analyzes why these problems are not discovered with traditional unit testing or acceptance testing. The findings are supported by citing examples from three recent embedded software development programs performed by the Johns Hopkins University Applied Physics Laboratory where formal stress testing was employed. It also defines what is meant by the robustness and elasticity of a software system. These findings will encourage software professionals to incorporate stress testing into their formal software development process. OUTLINE 1. INTRODUCTON 1.1 What can be learned by “breaking” the software 2. DESIGNING A STRESS TEST 2.1 What is a reasonable target CPU load? 2.2 Other ways to stress the system 2.3 Characteristics of a Stress Test 3. REAL WORLD RESULTS 3.1 Case #1: Software Missed Receiving Some Commands When CPU Was Heavily Loaded 3.2 Case #2: Processor Reset when Available Memory Buffers Were Exhausted 3.3 Case #3: Unexpected Command Rejection When CPU Was Heavily Loaded 3.4 Case #4: Processor Reset When RAM Disk Was Nearly Full 3.5 Synopsis of All Problems Found During Stress Testing 4. SUMMARY 1. INTRODUCTON Traditional Software Acceptance Testing is a standard phase in nearly every software development methodology. Test engineers develop and execute tests that are defined to validate software requirements. -
Testing Techniques Selection Based on SWOT Analysis
International Journal of Knowledge, Innovation and Entrepreneurship Volume 2 No. 1, 2014, pp. 56—68 Testing Techniques Selection Based on SWOT Analysis MUNAZZA JANNISAR, RUQIA BIBI & MUHAMMAD FAHAD KHAN University of Engineering and Technology, Pakistan Received 02 March 2014; received in revised form 15 April 2014; approved 22 April 2014 ABSTRACT Quality is easy to claim but hard to achieve. Testing is a most essential phase in software development life cycle not only to ensure a project’s success but also customer satisfaction. This paper presents SWOT Analysis of three testing tech- niques—White-Box, Black-Box and Grey Box. The testing techniques are evaluated on the basis of their strengths, weaknesses, opportunities and threats. The analysis in this paper shows that selection of the techniques should be based on a set of defined attrib- utes, context and objective. The findings in this paper might be helpful in highlighting and addressing issues related to testing techniques selection based on SWOT analysis. Keywords: Black Box Testing, White Box Testing, Grey Box, SWOT Introduction Software plays a substantial role in every sphere of life. It is a key reason why software engineering continually introducing new methodologies and improvement to software development. The capacity of organisations to achieve customer satisfaction or to cor- rectly identify the needs of customers can be misplaced, leading to ambiguities and un- wanted results 1. Researchers have suggested many testing techniques to deal with fault identification and removal subjects, before the product [software] is shipped to cus- tomer. Despite many verification and validation approaches to assuring product quality, defect-free software goal is not very often achieved.