Fuzzing for Software Security Testing and Quality Assurance Pdf
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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 -
A Study of Android Application Security
A Study of Android Application Security William Enck, Damien Octeau, Patrick McDaniel, and Swarat Chaudhuri Systems and Internet Infrastructure Security Laboratory Department of Computer Science and Engineering The Pennsylvania State University enck, octeau, mcdaniel, swarat @cse.psu.edu { } Abstract ingly desire it, markets are not in a position to provide security in more than a superficial way [30]. The lack of The fluidity of application markets complicate smart- a common definition for security and the volume of ap- phone security. Although recent efforts have shed light plications ensures that some malicious, questionable, and on particular security issues, there remains little insight vulnerable applications will find their way to market. into broader security characteristics of smartphone ap- In this paper, we broadly characterize the security of plications. This paper seeks to better understand smart- applications in the Android Market. In contrast to past phone application security by studying 1,100 popular studies with narrower foci, e.g., [14, 12], we consider a free Android applications. We introduce the ded decom- breadth of concerns including both dangerous functional- piler, which recovers Android application source code ity and vulnerabilities, and apply a wide range of analysis directly from its installation image. We design and exe- techniques. In this, we make two primary contributions: cute a horizontal study of smartphone applications based on static analysis of 21 million lines of recovered code. We design and implement a Dalvik decompilier, • Our analysis uncovered pervasive use/misuse of person- ded. ded recovers an application’s Java source al/phone identifiers, and deep penetration of advertising solely from its installation image by inferring lost and analytics networks. -
Types of Software Testing
Types of Software Testing We would be glad to have feedback from you. Drop us a line, whether it is a comment, a question, a work proposition or just a hello. You can use either the form below or the contact details on the rightt. Contact details [email protected] +91 811 386 5000 1 Software testing is the way of assessing a software product to distinguish contrasts between given information and expected result. Additionally, to evaluate the characteristic of a product. The testing process evaluates the quality of the software. You know what testing does. No need to explain further. But, are you aware of types of testing. It’s indeed a sea. But before we get to the types, let’s have a look at the standards that needs to be maintained. Standards of Testing The entire test should meet the user prerequisites. Exhaustive testing isn’t conceivable. As we require the ideal quantity of testing in view of the risk evaluation of the application. The entire test to be directed ought to be arranged before executing it. It follows 80/20 rule which expresses that 80% of defects originates from 20% of program parts. Start testing with little parts and extend it to broad components. Software testers know about the different sorts of Software Testing. In this article, we have incorporated majorly all types of software testing which testers, developers, and QA reams more often use in their everyday testing life. Let’s understand them!!! Black box Testing The black box testing is a category of strategy that disregards the interior component of the framework and spotlights on the output created against any input and performance of the system. -
Automated Web Application Testing Using Search Based Software Engineering
Automated Web Application Testing Using Search Based Software Engineering Nadia Alshahwan and Mark Harman CREST Centre University College London London, UK fnadia.alshahwan.10,[email protected] Abstract—This paper introduces three related algorithms and [21]. However, of 399 research papers on SBST,1 only one a tool, SWAT, for automated web application testing using Search [20] mentions web application testing issues and none applies Based Software Testing (SBST). The algorithms significantly search based test data generation to automate web application enhance the efficiency and effectiveness of traditional search based techniques exploiting both static and dynamic analysis. The testing. combined approach yields a 54% increase in branch coverage and Popular web development languages such as PHP and a 30% reduction in test effort. Each improvement is separately Python have characteristics that pose a challenge when ap- evaluated in an empirical study on 6 real world web applications. plying search based techniques such as dynamic typing and identifying the input vector. Moreover, the unique and rich Index Terms—SBSE; Automated Test data generation; Web nature of a web application’s output can be exploited to aid applications the test generation process and potentially improve effective- ness and efficiency. This was the motivation for our work: We seek to develop a search based approach to automated I. INTRODUCTION web application testing that overcomes challenges and takes advantage of opportunities that web applications offer. The importance of automated web application testing de- rives from the increasing reliance on these systems for busi- In this paper we introduce an automated search based ness, social, organizational and governmental functions. -
Smoke Testing What Is Smoke Testing?
Smoke Testing What is Smoke Testing? Smoke testing is the initial testing process exercised to check whether the software under test is ready/stable for further testing. The term ‘Smoke Testing’ is came from the hardware testing, in the hardware testing initial pass is done to check if it did not catch the fire or smoked in the initial switch on.Prior to start Smoke testing few test cases need to created once to use for smoke testing. These test cases are executed prior to start actual testing to checkcritical functionalities of the program is working fine. This set of test cases written such a way that all functionality is verified but not in deep. The objective is not to perform exhaustive testing, the tester need check the navigation’s & adding simple things, tester needs to ask simple questions “Can tester able to access software application?”, “Does user navigates from one window to other?”, “Check that the GUI is responsive” etc. Here are graphical representation of Smoke testing & Sanity testing in software testing: Smoke Sanity Testing Diagram The test cases can be executed manually or automated; this depends upon the project requirements. In this types of testing mainly focus on the important functionality of application, tester do not care about detailed testing of each software component, this can be cover in the further testing of application. The Smoke testing is typically executed by testers after every build is received for checking the build is in testable condition. This type of testing is applicable in the Integration Testing, System Testing and Acceptance Testing levels. -
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, -
The OWASP Application Security Program Quick Start Guide
Quick Start Guide The OWASP Application Security Program Quick Start Guide Five Days to Setting Up an Application Security Program Quickstart Guide About this Guide This guide is intended to be a short, straightforward introductory guide to standing-up or improving an Application Security Program1. The intended goal of the AppSec program is to implement measures throughout the code’s life- cycle to prevent gaps in the application security policy or the underlying system through flaws in the design, development, deployment, upgrade, or maintenance of the application. The application security program should effectively manage the security of its application systems, protecting information from unauthorized access, use, disclosure, disruption, modification, or destruction in order to provide integrity, confidentiality and availability. A fundamental component of this improved application security management is the ability to demonstrate acceptable levels of risk based on defined KPIs, including but limited to: 1. The number of vulnerabilities present in an application 2. The time to fix vulnerabilities 3. The remediation rate of vulnerabilities 4. The time vulnerabilities remain open The application security program deliverables include a holistic view of the state of security for each application, identifying the risks associated with the application and the countermeasures implemented to mitigate those risks, explaining how security is implemented, planning for system downtimes and emergencies, and providing a formal plan to improve the security in one or more of these areas. Audience The intended audience of this document is anyone from security engineers, developers, program managers, senior managers or a senior executive. This guide should be considered the start of a comprehensive approach, it is intended to give the basic questions and answers that should be asked by those who are in charge of the application security program in your organization, this includes those responsible for managing the risk of the entire organization. -
Web Gui Testing Checklist
Web Gui Testing Checklist Wes recrystallizing her quinone congruously, phytophagous and sulphonic. How imponderable is Schroeder when barbate whileand soft-footed Brewer gliff Zachery some incisure yakety-yak affluently. some chatoyancy? Fulgurating and battiest Nealson blossoms her amontillados refine Wbox aims to the field to be able to the automated support data, testing web gui checklist Planned testing techniques, including scripted testing, exploratory testing, and user experience testing. This gui content will the css or dynamic values? Test all input fields for special characters. For instance, create test data assist the maximum and minimum values in those data field. Assisted by timing testing is not tested to the order to achieve true black art relying on gui testing web checklist will best. The web hosting environments you start all web testing gui checklist can provide tests has had made. The gui testing procedures are the weak factors causing delays in agile here offering, gui testing web? At anytime without giving us a testing web gui checklist can also has on. How gui testing checklist for a gui testing web checklist to induce further eliminating redundant if there is transmitted without the below to use of jobs with. Monkey testing tool that an application or even perform testing web gui changes some test android scripts behind successful only allows an. Discusses the preceding css or if a sql injections through an application penetration testing on gui testing web? How much regression testing is enough? Fully automated attack simulations and highly automated fuzzing tests are appropriate here, and testers might also use domain testing to pursue intuitions. -
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. -
Parasoft Static Application Security Testing (SAST) for .Net - C/C++ - Java Platform
Parasoft Static Application Security Testing (SAST) for .Net - C/C++ - Java Platform Parasoft® dotTEST™ /Jtest (for Java) / C/C++test is an integrated Development Testing solution for automating a broad range of testing best practices proven to improve development team productivity and software quality. dotTEST / Java Test / C/C++ Test also seamlessly integrates with Parasoft SOAtest as an option, which enables end-to-end functional and load testing for complex distributed applications and transactions. Capabilities Overview STATIC ANALYSIS ● Broad support for languages and standards: Security | C/C++ | Java | .NET | FDA | Safety-critical ● Static analysis tool industry leader since 1994 ● Simple out-of-the-box integration into your SDLC ● Prevent and expose defects via multiple analysis techniques ● Find and fix issues rapidly, with minimal disruption ● Integrated with Parasoft's suite of development testing capabilities, including unit testing, code coverage analysis, and code review CODE COVERAGE ANALYSIS ● Track coverage during unit test execution and the data merge with coverage captured during functional and manual testing in Parasoft Development Testing Platform to measure true test coverage. ● Integrate with coverage data with static analysis violations, unit testing results, and other testing practices in Parasoft Development Testing Platform for a complete view of the risk associated with your application ● Achieve test traceability to understand the impact of change, focus testing activities based on risk, and meet compliance -
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.