Static Analysis the Workhorse of a End-To-End Securitye Testing Strategy
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List of Requirements for Code Reviews
WP2 DIGIT B1 - EP Pilot Project 645 Deliverable 9: List of Requirements for Code Reviews Specific contract n°226 under Framework Contract n° DI/07172 – ABCIII April 2016 DIGIT Fossa WP2 – Governance and Quality of Software Code – Auditing of Free and Open Source Software. Deliverable 9: List of requirements for code reviews Author: Disclaimer The information and views set out in this publication are those of the author(s) and do not necessarily reflect the official opinion of the Commission. The content, conclusions and recommendations set out in this publication are elaborated in the specific context of the EU – FOSSA project. The Commission does not guarantee the accuracy of the data included in this study. All representations, warranties, undertakings and guarantees relating to the report are excluded, particularly concerning – but not limited to – the qualities of the assessed projects and products. Neither the Commission nor any person acting on the Commission’s behalf may be held responsible for the use that may be made of the information contained herein. © European Union, 2016. Reuse is authorised, without prejudice to the rights of the Commission and of the author(s), provided that the source of the publication is acknowledged. The reuse policy of the European Commission is implemented by a Decision of 12 December 2011. Document elaborated in the specific context of the EU – FOSSA project. Reuse or reproduction authorised without prejudice to the Commission’s or the authors’ rights. Page 2 of 51 DIGIT Fossa WP2 – Governance and Quality of Software Code – Auditing of Free and Open Source Software. Deliverable 9: List of requirements for code reviews Contents CONTENTS............................................................................................................................................ -
Precise and Scalable Static Program Analysis of NASA Flight Software
Precise and Scalable Static Program Analysis of NASA Flight Software G. Brat and A. Venet Kestrel Technology NASA Ames Research Center, MS 26912 Moffett Field, CA 94035-1000 650-604-1 105 650-604-0775 brat @email.arc.nasa.gov [email protected] Abstract-Recent NASA mission failures (e.g., Mars Polar Unfortunately, traditional verification methods (such as Lander and Mars Orbiter) illustrate the importance of having testing) cannot guarantee the absence of errors in software an efficient verification and validation process for such systems. Therefore, it is important to build verification tools systems. One software error, as simple as it may be, can that exhaustively check for as many classes of errors as cause the loss of an expensive mission, or lead to budget possible. Static program analysis is a verification technique overruns and crunched schedules. Unfortunately, traditional that identifies faults, or certifies the absence of faults, in verification methods cannot guarantee the absence of errors software without having to execute the program. Using the in software systems. Therefore, we have developed the CGS formal semantic of the programming language (C in our static program analysis tool, which can exhaustively analyze case), this technique analyses the source code of a program large C programs. CGS analyzes the source code and looking for faults of a certain type. We have developed a identifies statements in which arrays are accessed out Of static program analysis tool, called C Global Surveyor bounds, or, pointers are used outside the memory region (CGS), which can analyze large C programs for embedded they should address. -
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. -
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 . -
Book of Abstracts
|zchhppts||jj fivétqrujznéqjsvkÂîñüìîé Ìåæäóíàðîäíî髯®µ¦±¦®·©© ±¡¨±¡¢¯³¸©«¯£©°¯¬½¨¯£¡³¦¬¦ª ²£¯¢¯¥®¯¤¯ °±¯¤±¡®¯¤¯¯¢¦²°¦¸¦®©À /LQX[9DFDWLRQ(DVWHUQ(XURSH2 ¤±¯¥®¯07Ĕ10èþíÿ2¤ ±¦²³ l¬½³¦±®¡³©£¡| 2 ÏbÇ ÈÈǹ Ì ºąºË®¯ËąÈ}ĆÒË®ikzº°Ċ}È cËąÈ}ĆÒºÓÓÈ«}ºããËĄÒ«ikzº°Ċ}sslȯÎÈÓ ik©Óĉ}ÒÓk|bÈą¯È cËĆËÓÏËÓ© Ñ.Ñ. Äåðå÷åííèê, êàíäèäàò òåõíè÷åñêèõ íàóê, äîöåíò, çàâåäóþùèé êàôåäðîé ýëåêòðîííûõ âû÷èñëèòåëüíûõ ìàøèí è ñèñòåì Áðåñòñêîãî ãîñóäàðñòâåííîãî òåõíè÷åñêîãî óíèâåðñèòåòà À.Â. Îòâàãèí, êàíäèäàò òåõíè÷åñêèõ íàóê, äîöåíò êàôåäðû ýëåêòðîííûõ âû÷èñëèòåëüíûõ ìàøèí Áåëîðóññêîãî óíèâåðñèòåòà èíôîðìàòèêè è ðàäèîýëåêòðîíèêè Ì |}¯©©ËË²ÓºãºĄÒÒñ¢¯±®©«¡³¦±©¡¬¯£Âîñüìîé̦§¥´- ®¡±¯¥®¯ª «¯®µ¦±¦®·©© ±¡¨±¡¢¯³¸©«¯£ ©°¯¬½¨¯£¡³¦¬¦ª²£¯- ¢¯¥®¯¤¯ °±¯¤±¡®¯¤¯ ¯¢¦²°¦¸¦®©À /LQX[ 9DFDWLRQ (DVWHUQ (XURSH2±¯¥®¯0710èþíÿ 2¤ °¯¥ ¯¢º¦ª ±¦¥ ¯²³¿«¡Ĕ±¦²³¬½³¦±®¡³©£¡Ĕ160² ,6%13070 Æxivétqrkv¡squjznéqjs, ïðåäñòàâëåííûå àâòîðàìè íà Âîñüìóþ Ìåæäóíàðîäíóþ êîíôåðåíöèþ ðàçðàáîò÷èêîâ è ïîëüçîâàòåëåé ñâîáîäíîãî ïðîãðàììíîãî îáåñïå÷åíèÿ Linux Vacation / Eastern Europe 2012, âêëþ÷àÿ âûåçäíóþ çèìíþþ ñåññèþ êîíôåðåíöèè LVEE Winter 2012. Ìàòåðèàëû äîêëàäîâ ïðåäñòàâëåíû íà ñàéòå êîíôåðåíöèè http://lvee.org è ðàñïðîñòðàíÿþòñÿ ïîä ëèöåíçèåé Creative Commons Attribution-ShareAlike 3.0. Ñòàòüè ïîñâÿùåíû íîâûì òåõíîëîãèÿì è ðàçðàáîòêàì â ñôåðå ñâîáîäíîãî (îòêðûòîãî) ïðîãðàììíîãî îáåñïå÷åíèÿ è çàòðàãèâàþò øèðîêèé ñïåêòð ïëàòôîðì – îò ðàáî÷èõ ñòàíöèé è ñåðâåðîâ, âêëþ÷àÿ ðåøåíèÿ íà áàçå âèðòóàëèçàöèè, äî âñòðàèâàåìûõ ñèñòåì è ìîáèëüíûõ óñòðîéñòâ. Ñáîðíèê ìîæåò áûòü èíòåðåñåí ñïåöèàëèñòàì â îáëàñòè èíôîðìàöè- -
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. -
Code Review Guide
CODE REVIEW GUIDE 2.0 RELEASE Project leaders: Larry Conklin and Gary Robinson Creative Commons (CC) Attribution Free Version at: https://www.owasp.org 1 F I 1 Forward - Eoin Keary Introduction How to use the Code Review Guide 7 8 10 2 Secure Code Review 11 Framework Specific Configuration: Jetty 16 2.1 Why does code have vulnerabilities? 12 Framework Specific Configuration: JBoss AS 17 2.2 What is secure code review? 13 Framework Specific Configuration: Oracle WebLogic 18 2.3 What is the difference between code review and secure code review? 13 Programmatic Configuration: JEE 18 2.4 Determining the scale of a secure source code review? 14 Microsoft IIS 20 2.5 We can’t hack ourselves secure 15 Framework Specific Configuration: Microsoft IIS 40 2.6 Coupling source code review and penetration testing 19 Programmatic Configuration: Microsoft IIS 43 2.7 Implicit advantages of code review to development practices 20 2.8 Technical aspects of secure code review 21 2.9 Code reviews and regulatory compliance 22 5 A1 3 Injection 51 Injection 52 Blind SQL Injection 53 Methodology 25 Parameterized SQL Queries 53 3.1 Factors to Consider when Developing a Code Review Process 25 Safe String Concatenation? 53 3.2 Integrating Code Reviews in the S-SDLC 26 Using Flexible Parameterized Statements 54 3.3 When to Code Review 27 PHP SQL Injection 55 3.4 Security Code Review for Agile and Waterfall Development 28 JAVA SQL Injection 56 3.5 A Risk Based Approach to Code Review 29 .NET Sql Injection 56 3.6 Code Review Preparation 31 Parameter collections 57 3.7 Code Review Discovery and Gathering the Information 32 3.8 Static Code Analysis 35 3.9 Application Threat Modeling 39 4.3.2. -
Introduction to Yasca
Introduction To Yasca Presented at NYPHP 24 February 2009 Michael V. Scovetta Agenda . Who Am I? . What is Yasca? . How does it work? . Requirements . How should I use it? . The Future of Yasca . Demonstration . Questions? 2 Who Am I? . Development . CA ~2002 . Perl, Java, PHP . Information Security . UBS ~2005 . Security Consulting . Cigital ~2008 . Architecture . CA ~2008 3 What is Yasca? . Yasca started as a set of perl scripts that grepped through source code looking for XSS vulnerabilities. <%=request.getParameter("foo")%> . <?=$_REQUEST["foo"]?> . Then I needed to do multi-line searches: . String s = request.getParameter("foo"); out.println(s); . As I wrote more rules, I found other scanners that already had many of them. So I made calls out to them. Then everything got nasty and I wrote it all from scratch again in PHP. 4 What is Yasca? . Yasca is an open-source tool that can help you analyze program source code. It leverages several static analysis tools. PMD (http://pmd.sourceforge.net/) . J-Lint (http://artho.com/jlint/) . Pixy (http://pixybox.seclab.tuwien.ac.at/pixy/) . FindBugs (http://findbugs.sourceforge.net/) . It can be used to scan virtually any file type, not only traditional source code. Yasca is written in command-line PHP and released under the BSD license. 5 How Does it Work? . Architecture based on plug-ins. "Major Plug-in" => calls another tool to do the scan . e.g. PMD, J-Lint, FindBugs, Pixy, Grep . "Minor Plug-in" => uses embedded logic . Relatively easy to write, extremely flexible Report Plug-in Yasca Plug-in Generator Plug-in Output /tmp/my_source_code 6 How Does it Work .