Precise and Scalable Static Program Analysis of NASA Flight Software
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Static Analysis the Workhorse of a End-To-End Securitye Testing Strategy
Static Analysis The Workhorse of a End-to-End Securitye Testing Strategy Achim D. Brucker [email protected] http://www.brucker.uk/ Department of Computer Science, The University of Sheffield, Sheffield, UK Winter School SECENTIS 2016 Security and Trust of Next Generation Enterprise Information Systems February 8–12, 2016, Trento, Italy Static Analysis: The Workhorse of a End-to-End Securitye Testing Strategy Abstract Security testing is an important part of any security development lifecycle (SDL) and, thus, should be a part of any software (development) lifecycle. Still, security testing is often understood as an activity done by security testers in the time between “end of development” and “offering the product to customers.” Learning from traditional testing that the fixing of bugs is the more costly the later it is done in development, security testing should be integrated, as early as possible, into the daily development activities. The fact that static analysis can be deployed as soon as the first line of code is written, makes static analysis the right workhorse to start security testing activities. In this lecture, I will present a risk-based security testing strategy that is used at a large European software vendor. While this security testing strategy combines static and dynamic security testing techniques, I will focus on static analysis. This lecture provides a introduction to the foundations of static analysis as well as insights into the challenges and solutions of rolling out static analysis to more than 20000 developers, distributed across the whole world. A.D. Brucker The University of Sheffield Static Analysis February 8–12., 2016 2 Today: Background and how it works ideally Tomorrow: (Ugly) real world problems and challenges (or why static analysis is “undecideable” in practice) Our Plan A.D. -
Abstract Interpretation
Colloquium d’informatique de l’UPMC Sorbonne Universités Abstract Interpretation 29 septembre 2016, 18:00, Amphi 15 4 Place Jussieu, 75005 Paris Patrick Cousot [email protected]@yu.e1du cs.nyu.edu/~pcousot Abstract interpretation, Colloquium d’informatique de l’UPMC Sorbonne Universités, 29 Septembre 2016 1 © P. Cousot This is an abstract interpretation Abstract interpretation, Colloquium d’informatique de l’UPMC Sorbonne Universités, 29 Septembre 2016 2 © P. Cousot Scientific research Abstract interpretation, Colloquium d’informatique de l’UPMC Sorbonne Universités, 29 Septembre 2016 3 © P. Cousot Scientific research • In Mathematics/Physics: trend towards unification and synthesis through universal principles • In Computer science: trend towards dispersion and parcellation through a ever-growing collection of local ad-hoc techniques for specific applications An exponential process, will stop! Abstract interpretation, Colloquium d’informatique de l’UPMC Sorbonne Universités, 29 Septembre 2016 4 © P. Cousot Example: reasoning on computational structures WCET Operational Security protocole Systems biology Axiomatic verification semantics semantics analysis Abstraction Dataflow Model Database refinement Confidentiality checking analysis analysis query Type Partial Obfuscation Dependence Program evaluation inference synthesis Denotational analysis Separation Effect logic Grammar systems semantics CEGAR analysis Theories Program Termination Statistical Trace combination transformation proof semantics model-checking Interpolants Abstract Shape Code analysis -
Static Program Analysis Via 3-Valued Logic
Static Program Analysis via 3-Valued Logic ¡ ¢ £ Thomas Reps , Mooly Sagiv , and Reinhard Wilhelm ¤ Comp. Sci. Dept., University of Wisconsin; [email protected] ¥ School of Comp. Sci., Tel Aviv University; [email protected] ¦ Informatik, Univ. des Saarlandes;[email protected] Abstract. This paper reviews the principles behind the paradigm of “abstract interpretation via § -valued logic,” discusses recent work to extend the approach, and summarizes on- going research aimed at overcoming remaining limitations on the ability to create program- analysis algorithms fully automatically. 1 Introduction Static analysis concerns techniques for obtaining information about the possible states that a program passes through during execution, without actually running the program on specific inputs. Instead, static-analysis techniques explore a program’s behavior for all possible inputs and all possible states that the program can reach. To make this feasible, the program is “run in the aggregate”—i.e., on abstract descriptors that repre- sent collections of many states. In the last few years, researchers have made important advances in applying static analysis in new kinds of program-analysis tools for identi- fying bugs and security vulnerabilities [1–7]. In these tools, static analysis provides a way in which properties of a program’s behavior can be verified (or, alternatively, ways in which bugs and security vulnerabilities can be detected). Static analysis is used to provide a safe answer to the question “Can the program reach a bad state?” Despite these successes, substantial challenges still remain. In particular, pointers and dynamically-allocated storage are features of all modern imperative programming languages, but their use is error-prone: ¨ Dereferencing NULL-valued pointers and accessing previously deallocated stor- age are two common programming mistakes. -
Opportunities and Open Problems for Static and Dynamic Program Analysis Mark Harman∗, Peter O’Hearn∗ ∗Facebook London and University College London, UK
1 From Start-ups to Scale-ups: Opportunities and Open Problems for Static and Dynamic Program Analysis Mark Harman∗, Peter O’Hearn∗ ∗Facebook London and University College London, UK Abstract—This paper1 describes some of the challenges and research questions that target the most productive intersection opportunities when deploying static and dynamic analysis at we have yet witnessed: that between exciting, intellectually scale, drawing on the authors’ experience with the Infer and challenging science, and real-world deployment impact. Sapienz Technologies at Facebook, each of which started life as a research-led start-up that was subsequently deployed at scale, Many industrialists have perhaps tended to regard it unlikely impacting billions of people worldwide. that much academic work will prove relevant to their most The paper identifies open problems that have yet to receive pressing industrial concerns. On the other hand, it is not significant attention from the scientific community, yet which uncommon for academic and scientific researchers to believe have potential for profound real world impact, formulating these that most of the problems faced by industrialists are either as research questions that, we believe, are ripe for exploration and that would make excellent topics for research projects. boring, tedious or scientifically uninteresting. This sociological phenomenon has led to a great deal of miscommunication between the academic and industrial sectors. I. INTRODUCTION We hope that we can make a small contribution by focusing on the intersection of challenging and interesting scientific How do we transition research on static and dynamic problems with pressing industrial deployment needs. Our aim analysis techniques from the testing and verification research is to move the debate beyond relatively unhelpful observations communities to industrial practice? Many have asked this we have typically encountered in, for example, conference question, and others related to it. -
DEVELOPING SECURE SOFTWARE T in an AGILE PROCESS Dejan
Software - in an - in Software Developing Secure aBSTRACT Background: Software developers are facing in- a real industry setting. As secondary methods for creased pressure to lower development time, re- data collection a variety of approaches have been Developing Secure Software lease new software versions more frequent to used, such as semi-structured interviews, work- customers and to adapt to a faster market. This shops, study of literature, and use of historical data - in an agile proceSS new environment forces developers and companies from the industry. to move from a plan based waterfall development process to a flexible agile process. By minimizing Results: The security engineering best practices the pre development planning and instead increa- were investigated though a series of case studies. a sing the communication between customers and The base agile and security engineering compati- gile developers, the agile process tries to create a new, bility was assessed in literature, by developers and more flexible way of working. This new way of in practical studies. The security engineering best working allows developers to focus their efforts on practices were group based on their purpose and p the features that customers want. With increased their compatibility with the agile process. One well roce connectability and the faster feature release, the known and popular best practice, automated static Dejan Baca security of the software product is stressed. To de- code analysis, was toughly investigated for its use- velop secure software, many companies use secu- fulness, deployment and risks of using as part of SS rity engineering processes that are plan heavy and the process. -
Using Static Program Analysis to Aid Intrusion Detection
Using Static Program Analysis to Aid Intrusion Detection Manuel Egele, Martin Szydlowski, Engin Kirda, and Christopher Kruegel Secure Systems Lab Technical University Vienna fpizzaman,msz,ek,[email protected] Abstract. The Internet, and in particular the world-wide web, have be- come part of the everyday life of millions of people. With the growth of the web, the demand for on-line services rapidly increased. Today, whole industry branches rely on the Internet to do business. Unfortunately, the success of the web has recently been overshadowed by frequent reports of security breaches. Attackers have discovered that poorly written web applications are the Achilles heel of many organizations. The reason is that these applications are directly available through firewalls and are of- ten developed by programmers who focus on features and tight schedules instead of security. In previous work, we developed an anomaly-based intrusion detection system that uses learning techniques to identify attacks against web- based applications. That system focuses on the analysis of the request parameters in client queries, but does not take into account any infor- mation about the protected web applications themselves. The result are imprecise models that lead to more false positives and false negatives than necessary. In this paper, we describe a novel static source code analysis approach for PHP that allows us to incorporate information about a web application into the intrusion detection models. The goal is to obtain a more precise characterization of web request parameters by analyzing their usage by the program. This allows us to generate more precise intrusion detection models. -
Engineering of Reliable and Secure Software Via Customizable Integrated Compilation Systems
Engineering of Reliable and Secure Software via Customizable Integrated Compilation Systems Zur Erlangung des akademischen Grades eines Doktors der Ingenieurwissenschaften von der KIT-Fakultät für Informatik des Karlsruher Institut für Technologie (KIT) genehmigte Dissertation von Dipl.-Inf. Oliver Scherer Tag der mündlichen Prüfung: 06.05.2021 1. Referent: Prof. Dr. Veit Hagenmeyer 2. Referent: Prof. Dr. Ralf Reussner This document is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0): https://creativecommons.org/licenses/by-sa/4.0/deed.en Abstract Lack of software quality can cause enormous unpredictable costs. Many strategies exist to prevent or detect defects as early in the development process as possible and can generally be separated into proactive and reactive measures. Proactive measures in this context are schemes where defects are avoided by planning a project in a way that reduces the probability of mistakes. They are expensive upfront without providing a directly visible benefit, have low acceptance by developers or don’t scale with the project. On the other hand, purely reactive measures only fix bugs as they are found and thus do not yield any guarantees about the correctness of the project. In this thesis, a new method is introduced, which allows focusing on the project specific issues and decreases the discrepancies between the abstract system model and the final software product. The first component of this method isa system that allows any developer in a project to implement new static analyses and integrate them into the project. The integration is done in a manner that automatically prevents any other project developer from accidentally violating the rule that the new static analysis checks. -
Lecture Notes in Computer Science 1145 Edited by G
Lecture Notes in Computer Science 1145 Edited by G. Goos, J. Hartmanis and J. van Leeuwen Advisory Board: W. Brauer D. Gries J. Stoer Radhia Cousot David A. Schmidt (Eds.) Static Analysis Third International Symposium, SAS '96 Aachen, Germany, September 24-26, 1996 Proceedings ~ Springer Series Editors Gerhard Goos, Karlsruhe University, Germany Juris Hartmanis, Cornell University, NY, USA Jan van Leeuwen, Utrecht University, The Netherlands Volume Editors Radhia Cousot l~cole Polytechnique, Laboratoire d'Inforrnatique F-91128 Palaiseau Cedex, France E-mail: radhia.cousot @lix.polytechnique.fr David A. Schmidt Kansas State University, Department of Computing and Information Sciences Manhattan, KS 66506, USA E-maih [email protected] Cataloging-in-Publication data applied for Die Deutsche Bibliothek - CIP-Einheitsaufnahme Static analysis : third international symposium ; proceedings / SAS '96, Aachen, Germany, September 24 - 26, 1996. Radhia Cousot ; David A. Schmidt (ed.). - Berlin ; Heidelberg ; New York ; Barcelona ; Budapest ; Hong Kong ; London ; Milan ; Paris ; Santa Clara ; Singapore ; Tokyo : Springer, 1996 (Lecture notes in computer science ; Vol. 1145) ISBN 3-540-61739-6 NE: Cousot, Radhia [Hrsg.]; SAS <3, 1996, Aachen>; GT CR Subject Classification (1991): D.1, D.2.8, D.3.2-3,F.3.1-2, F.4.2 ISSN 0302-9743 ISBN 3-540-61739-6 Springer-Verlag Berlin Heidelberg New York This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer -Verlag. -
Introduction to Static Analysis
Introduction to Static Analysis 17-654: Analysis of Software Artifacts Jonathan Aldrich 2/21/2011 17-654: Analysis of Software Artifacts 1 Static Analysis Source: Engler et al., Checking System Rules Using System-Specific, Programmer-Written Find the Bug! Compiler Extensions , OSDI ’00. disable interrupts ERROR: returning with interrupts disabled re-enable interrupts 2/21/2011 17-654: Analysis of Software Artifacts 2 Static Analysis 1 Metal Interrupt Analysis Source: Engler et al., Checking System Rules Using System-Specific, Programmer-Written Compiler Extensions , OSDI ’00. enable => err(double enable) is_enabled enable disable is_disabled end path => err(end path with/intr disabled) disable => err(double disable) 2/21/2011 17-654: Analysis of Software Artifacts 3 Static Analysis Source: Engler et al., Checking System Rules Using System-Specific, Programmer-Written Applying the Analysis Compiler Extensions , OSDI ’00. initial state is_enabled transition to is_disabled final state is_disabled: ERROR! transition to is_enabled final state is_enabled is OK 2/21/2011 17-654: Analysis of Software Artifacts 4 Static Analysis 2 Outline • Why static analysis? • The limits of testing and inspection • What is static analysis? • How does static analysis work? • AST Analysis • Dataflow Analysis 2/21/2011 17-654: Analysis of Software Artifacts 5 Static Analysis 2/21/2011 17-654: Analysis of Software Artifacts 6 Static Analysis 3 Process, Cost, and Quality Slide: William Scherlis Process intervention, Additional technology testing, and inspection and tools are needed to yield first-order close the gap software quality improvement Perfection (unattainable) Critical Systems Acceptability Software Quality Process CMM: 1 2 3 4 5 Rigor, Cost S&S, Agile, RUP, etc: less rigorous . -
Automated Large-Scale Multi-Language Dynamic Program
Automated Large-Scale Multi-Language Dynamic Program Analysis in the Wild Alex Villazón Universidad Privada Boliviana, Bolivia [email protected] Haiyang Sun Università della Svizzera italiana, Switzerland [email protected] Andrea Rosà Università della Svizzera italiana, Switzerland [email protected] Eduardo Rosales Università della Svizzera italiana, Switzerland [email protected] Daniele Bonetta Oracle Labs, United States [email protected] Isabella Defilippis Universidad Privada Boliviana, Bolivia isabelladefi[email protected] Sergio Oporto Universidad Privada Boliviana, Bolivia [email protected] Walter Binder Università della Svizzera italiana, Switzerland [email protected] Abstract Today’s availability of open-source software is overwhelming, and the number of free, ready-to-use software components in package repositories such as NPM, Maven, or SBT is growing exponentially. In this paper we address two straightforward yet important research questions: would it be possible to develop a tool to automate dynamic program analysis on public open-source software at a large scale? Moreover, and perhaps more importantly, would such a tool be useful? We answer the first question by introducing NAB, a tool to execute large-scale dynamic program analysis of open-source software in the wild. NAB is fully-automatic, language-agnostic, and can scale dynamic program analyses on open-source software up to thousands of projects hosted in code repositories. Using NAB, we analyzed more than 56K Node.js, Java, and Scala projects. Using the data collected by NAB we were able to (1) study the adoption of new language constructs such as JavaScript Promises, (2) collect statistics about bad coding practices in JavaScript, and (3) identify Java and Scala task-parallel workloads suitable for inclusion in a domain-specific benchmark suite. -
On Abstraction in Software Verification ‹
On Abstraction in Software Verification ‹ Patrick Cousot1 and Radhia Cousot2 1 École normale supérieure, Département d'informatique, 45 rue d'Ulm, 75230 Paris cedex 05, France [email protected] www.di.ens.fr/~cousot/ 2 CNRS & École polytechnique, Laboratoire d'informatique, 91128 Palaiseau cedex, France [email protected] lix.polytechnique.fr/~rcousot Abstract. We show that the precision of static abstract software check- ing algorithms can be enhanced by taking explicitly into account the ab- stractions that are involved in the design of the program model/abstract semantics. This is illustrated on reachability analysis and abstract test- ing. 1 Introduction Most formal methods for reasoning about programs (such as deductive meth- ods, software model checking, dataflow analysis) do not reason directly on the trace-based operational program semantics but on an approximate model of this semantics. The abstraction involved in building the model of the program seman- tics is usually left implicit and not discussed. The importance of this abstraction appears when it is made explicit for example in order to discuss the soundness and (in)completeness of temporal-logic based verification methods [1, 2]. The purpose of this paper is to discuss the practical importance of this ab- straction when designing static software checking algorithms. This is illustrated on reachability analysis and abstract testing. 2 Transition Systems We follow [3, 4] in formalizing a hardware or software computer system by a transition system xS; t; I; F; Ey with set of states S, transition relation t Ď pS ˆ Sq, initial states I Ď S, erroneous states E Ď S, and final states F Ď S. -
Caterina Urban
CATERINA URBAN DATE AND PLACE OF BIRTH March 9th, 1987, Udine, Italy NATIONALITY Italian ADDRESS École Normale Supérieure, 45 rue d’Ulm, 75005 Paris, France EMAIL [email protected] WEBPAGE https://caterinaurban.github.io DBLP http://dblp.org/pers/hd/u/Urban:Caterina GOOGLE SCHOLAR http://scholar.google.it/citations?user=4-u1_HIAAAAJ CURRENT POSITION • INRIA, Paris, France — Research Scientist (Chargé de Recherche), Feb 2019 - Now EDUCATION • École Normale Supérieure, Paris, France — Ph.D. in Computer Science, Dec 2011 - July 2015 Subject: Static Analysis by Abstract Interpretation of Functional Temporal Properties of Programs Advisors: Radhia Cousot (Emeritus Research Director, CNRS, Paris, France) and Antoine Miné (Research Scientist, CRNS, Paris, France) Final mark: summa cum laude • Menlo College, Atherton, USA — Fifth Summer School on Formal Techniques, May 2015 • Università degli Studi di Udine, Italy — Master’s degree in Computer Science, Fall 2009 - Fall 2011 Final mark: summa cum laude • Università degli Studi di Udine, Italy — Bachelor’s degree in Computer Science, Fall 2006 - Fall 2009 Final mark: summa cum laude GRANTS • Industrial Grant, Fujitsu: “Formal Verification Techniques for Machine Learning Systems”, Oct 2021 - Sep 2022 • Industrial Grant, Airbus: “State of the Art in Formal Methods for Artificial Intelligence”, 2020 • Principal Investigator, ETH Career Seed Grant, ETH Zurich: “Static Analysis for Data Science Applications”, 30kCHF, Jan 2017 - Dec 2017 AWARDS AND HONORS • Invited Paper at IJCAI 2016 - Sister Conference