Fuzzing for Software Security Testing and Quality Assurance Ch00fm 5053.Qxp 5/19/08 12:45 PM Page Ii
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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 -
Core Elements of Continuous Testing
WHITE PAPER CORE ELEMENTS OF CONTINUOUS TESTING Today’s modern development disciplines -- whether Agile, Continuous Integration (CI) or Continuous Delivery (CD) -- have completely transformed how teams develop and deliver applications. Companies that need to compete in today’s fast-paced digital economy must also transform how they test. Successful teams know the secret sauce to delivering high quality digital experiences fast is continuous testing. This paper will define continuous testing, explain what it is, why it’s important, and the core elements and tactical changes development and QA teams need to make in order to succeed at this emerging practice. TABLE OF CONTENTS 3 What is Continuous Testing? 6 Tactical Engineering Considerations 3 Why Continuous Testing? 7 Benefits of Continuous Testing 4 Core Elements of Continuous Testing WHAT IS CONTINUOUS TESTING? Continuous testing is the practice of executing automated tests throughout the software development cycle. It’s more than just automated testing; it’s applying the right level of automation at each stage in the development process. Unlike legacy testing methods that occur at the end of the development cycle, continuous testing occurs at multiple stages, including development, integration, pre-release, and in production. Continuous testing ensures that bugs are caught and fixed far earlier in the development process, improving overall quality while saving significant time and money. WHY CONTINUOUS TESTING? Continuous testing is a critical requirement for organizations that are shifting left towards CI or CD, both modern development practices that ensure faster time to market. When automated testing is coupled with a CI server, tests can instantly be kicked off with every build, and alerts with passing or failing test results can be delivered directly to the development team in real time. -
Effectiveness of Software Testing Techniques in Enterprise: a Case Study
MYKOLAS ROMERIS UNIVERSITY BUSINESS AND MEDIA SCHOOL BRIGITA JAZUKEVIČIŪTĖ (Business Informatics) EFFECTIVENESS OF SOFTWARE TESTING TECHNIQUES IN ENTERPRISE: A CASE STUDY Master Thesis Supervisor – Assoc. Prof. Andrej Vlasenko Vilnius, 2016 CONTENTS INTRODUCTION .................................................................................................................................. 7 1. THE RELATIONSHIP BETWEEN SOFTWARE TESTING AND SOFTWARE QUALITY ASSURANCE ........................................................................................................................................ 11 1.1. Introduction to Software Quality Assurance ......................................................................... 11 1.2. The overview of Software testing fundamentals: Concepts, History, Main principles ......... 20 2. AN OVERVIEW OF SOFTWARE TESTING TECHNIQUES AND THEIR USE IN ENTERPRISES ...................................................................................................................................... 26 2.1. Testing techniques as code analysis ....................................................................................... 26 2.1.1. Static testing ...................................................................................................................... 26 2.1.2. Dynamic testing ................................................................................................................. 28 2.2. Test design based Techniques ............................................................................................... -
Studying the Feasibility and Importance of Software Testing: an Analysis
Dr. S.S.Riaz Ahamed / Internatinal Journal of Engineering Science and Technology Vol.1(3), 2009, 119-128 STUDYING THE FEASIBILITY AND IMPORTANCE OF SOFTWARE TESTING: AN ANALYSIS Dr.S.S.Riaz Ahamed Principal, Sathak Institute of Technology, Ramanathapuram,India. Email:[email protected], [email protected] ABSTRACT Software testing is a critical element of software quality assurance and represents the ultimate review of specification, design and coding. Software testing is the process of testing the functionality and correctness of software by running it. Software testing is usually performed for one of two reasons: defect detection, and reliability estimation. The problem of applying software testing to defect detection is that software can only suggest the presence of flaws, not their absence (unless the testing is exhaustive). The problem of applying software testing to reliability estimation is that the input distribution used for selecting test cases may be flawed. The key to software testing is trying to find the modes of failure - something that requires exhaustively testing the code on all possible inputs. Software Testing, depending on the testing method employed, can be implemented at any time in the development process. Keywords: verification and validation (V & V) 1 INTRODUCTION Testing is a set of activities that could be planned ahead and conducted systematically. The main objective of testing is to find an error by executing a program. The objective of testing is to check whether the designed software meets the customer specification. The Testing should fulfill the following criteria: ¾ Test should begin at the module level and work “outward” toward the integration of the entire computer based system. -
ON SOFTWARE TESTING and SUBSUMING MUTANTS an Empirical Study
ON SOFTWARE TESTING AND SUBSUMING MUTANTS An empirical study Master Degree Project in Computer Science Advanced level 15 credits Spring term 2014 András Márki Supervisor: Birgitta Lindström Examiner: Gunnar Mathiason Course: DV736A WECOA13: Web Computing Magister Summary Mutation testing is a powerful, but resource intense technique for asserting software quality. This report investigates two claims about one of the mutation operators on procedural logic, the relation operator replacement (ROR). The constrained ROR mutant operator is a type of constrained mutation, which targets to lower the number of mutants as a “do smarter” approach, making mutation testing more suitable for industrial use. The findings in the report shows that the hypothesis on subsumption is rejected if mutants are to be detected on function return values. The second hypothesis stating that a test case can only detect a single top-level mutant in a subsumption graph is also rejected. The report presents a comprehensive overview on the domain of mutation testing, displays examples of the masking behaviour previously not described in the field of mutation testing, and discusses the importance of the granularity where the mutants should be detected under execution. The contribution is based on literature survey and experiment. The empirical findings as well as the implications are discussed in this master dissertation. Keywords: Software Testing, Mutation Testing, Mutant Subsumption, Relation Operator Replacement, ROR, Empirical Study, Strong Mutation, Weak Mutation -
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. -
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. -
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. -
Acceptance Testing Tools - a Different Perspective on Managing Requirements
Acceptance Testing Tools - A different perspective on managing requirements Wolfgang Emmerich Professor of Distributed Computing University College London http://sse.cs.ucl.ac.uk Learning Objectives • Introduce the V-Model of quality assurance • Stress the importance of testing in terms of software engineering economics • Understand that acceptance tests are requirements specifications • Introduce acceptance and integration testing tools for Test Driven Development • Appreciate that automated acceptance tests are executable requirements specifications 2 V-Model in Distributed System Development Requirements Acceptance Test Software Integration Architecture Test Detailed System Design Test See: B. Boehm Guidelines for Verifying and Validating Software Unit Requirements and Design Code Specifications. Euro IFIP, P. A. Test Samet (editor), North-Holland Publishing Company, IFIP, 1979. 3 1 Traditional Software Development Requirements Acceptance Test Software Integration Architecture Test Detailed System Design Test Unit Code Test 4 Test Driven Development of Distributed Systems Use Cases/ User Stories Acceptance QoS Requirements Test Software Integration & Architecture System Test Detailed Unit Design Test These tests Code should be automated 5 Advantages of Test Driven Development • Early definition of acceptance tests reveals incomplete requirements • Early formalization of requirements into automated acceptance tests unearths ambiguities • Flaws in distributed software architectures (there often are many!) are discovered early • Unit tests become precise specifications • Early resolution improves productivity (see next slide) 6 2 Software Engineering Economics See: B. Boehm: Software Engineering Economics. Prentice Hall. 1981 7 An Example Consider an on-line car dealership User Story: • I first select a locale to determine the language shown at the user interface. I then select the SUV I want to buy. -
Model-Based Fuzzing Using Symbolic Transition Systems
Model-Based Fuzzing Using Symbolic Transition Systems Wouter Bohlken [email protected] January 31, 2021, 48 pages Academic supervisor: Dr. Ana-Maria Oprescu, [email protected] Daily supervisor: Dr. Machiel van der Bijl, [email protected] Host organisation: Axini, https://www.axini.com Universiteit van Amsterdam Faculteit der Natuurwetenschappen, Wiskunde en Informatica Master Software Engineering http://www.software-engineering-amsterdam.nl Abstract As software is getting more complex, the need for thorough testing increases at the same rate. Model- Based Testing (MBT) is a technique for thorough functional testing. Model-Based Testing uses a formal definition of a program and automatically extracts test cases. While MBT is useful for functional testing, non-functional security testing is not covered in this approach. Software vulnerabilities, when exploited, can lead to serious damage in industry. Finding flaws in software is a complicated, laborious, and ex- pensive task, therefore, automated security testing is of high relevance. Fuzzing is one of the most popular and effective techniques for automatically detecting vulnerabilities in software. Many differ- ent fuzzing approaches have been developed in recent years. Research has shown that there is no single fuzzer that works best on all types of software, and different fuzzers should be used for different purposes. In this research, we conducted a systematic review of state-of-the-art fuzzers and composed a list of candidate fuzzers that can be combined with MBT. We present two approaches on how to combine these two techniques: offline and online. An offline approach fully utilizes an existing fuzzer and automatically extracts relevant information from a model, which is then used for fuzzing. -
An Analysis of Current Guidance in the Certification of Airborne Software
An Analysis of Current Guidance in the Certification of Airborne Software by Ryan Erwin Berk B.S., Mathematics I Massachusetts Institute of Technology, 2002 B.S., Management Science I Massachusetts Institute of Technology, 2002 Submitted to the System Design and Management Program In Partial Fulfillment of the Requirements for the Degree of Master of Science in Engineering and Management at the ARCHIVES MASSACHUSETrS INS E. MASSACHUSETTS INSTITUTE OF TECHNOLOGY OF TECHNOLOGY June 2009 SEP 2 3 2009 © 2009 Ryan Erwin Berk LIBRARIES All Rights Reserved The author hereby grants to MIT permission to reproduce and to distribute publicly paper and electronic copies of this thesis document in whole or in part in any medium now known or hereafter created. Signature of Author Ryan Erwin Berk / System Design & Management Program May 8, 2009 Certified by _ Nancy Leveson Thesis Supervisor Professor of Aeronautics and Astronautics pm-m A 11A Professor of Engineering Systems Accepted by _ Patrick Hale Director System Design and Management Program This page is intentionally left blank. An Analysis of Current Guidance in the Certification of Airborne Software by Ryan Erwin Berk Submitted to the System Design and Management Program on May 8, 2009 in Partial Fulfillment of the Requirements for the Degree of Master of Science in Engineering and Management ABSTRACT The use of software in commercial aviation has expanded over the last two decades, moving from commercial passenger transport down into single-engine piston aircraft. The most comprehensive and recent official guidance on software certification guidelines was approved in 1992 as DO-178B, before the widespread use of object-oriented design and complex aircraft systems integration in general aviation (GA). -
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.