JITANA: a Modern Hybrid Program Analysis Framework for Android Platforms
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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. -
AV-TEST Security Report for 2016/2017
FACTS AND FIGURES SECURITY REPORT The AV-TEST Security Report 2 WINDOWS Security Status 5 macOS Security Status 10 ANDROID Security Status 13 INTERNET THREATS Security Status 16 IoT Security Status 19 2016/17 Test Statistics 22 FACTS AND FIGURES Declining malware statistics It remains positive to note that the declining malware trend in 2016 The AV-TEST provided some relief, at least quantitatively. Thus, compared to 2015, detection systems were required to seek out and defend against 14% fewer Security Report malware samples. In total, this amounted to precisely 11,725,292 fewer newly developed malware programs than in the previous year. It should not be The best news right off the bat: forgotten, however, that the volume of newly developed malware in 2016 still represented the second-highest since the beginning of measurements by Compared to the previous year, the AV-TEST systems. In addition, 2015 saw skyrocketing growth in malware the detection systems of AV-TEST showed programs and in comparison to 2014, practically a doubling of the sample statistics. The overall number of malware programs for all operating systems a slight decline in the development currently exceeds 640 million. of malware programs for the year 2016. Without wanting to belittle the positive trend for 2016, the fact remains that Overall, that is a pleasing trend, however there have been several short-term downward trends since the beginning of by no means any reason to celebrate, measurements in 1984, a total of six times, without seriously influencing the clear, long-term trend – towards more malware. Despite declining numbers, as evidenced by the AV-TEST Institute‘s in 2016, the AV-TEST analysis systems still recorded an average of 350,000 statistics of this year‘s Security Report. -
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. -
Global 2000 Bank Secures 9,000 Android Smartphones to Fulfill Internal Compliance Requirements
CASE STUDY Global 2000 bank secures 9,000 Android smartphones to fulfill internal compliance requirements Customer Profile This financial services firm is based in the middle east, has an international network of 1400 branches globally, and is a member of the Forbes Global 2000 list. Industry: Financial services Mobility Policy: COPE EMM Solution: VMware AirWatch The Solution The Challenge • Lookout Mobile Endpoint Security To enable their Corporate Owned, Personally Enabled (COPE) mobility policy, The Results this leading bank needed a mobile security solution that would comply with their • Achieved compliance with internal internal policy for data protection, integrate with VMware AirWatch, and provide policies for endpoint protection visibility into mobile threats encountered by their international workforce. • Gained visibility into high-risk The IT team decided to implement a COPE mobility policy in order to reduce threats support time by having a limited number of device models and Android versions • Improved employee productivity to maintain. In addition, the bank has developed their own enterprise application with no increase in support tickets that enables their employees to deliver banking services to customers via mobile devices. With no visibility into threats or data leakage on mobile devices, the IT mobility team knew that their unprotected mobile endpoints were an attack surface that presented a major security risk. 1 CASE STUDY The Results Lookout delivers a solution that collects The bank is very happy with how quickly they were able to “ deploy Lookout, including pushing the Lookout For Work app threat data from around the world, and out to 2,000 devices a day towards the end of the process. -
VOL.80 August, 2016 ASEC REPORT VOL.80 August, 2016
Security Trend ASEC REPORT VOL.80 August, 2016 ASEC REPORT VOL.80 August, 2016 ASEC (AhnLab Security Emergency Response Center) is a global security response group consisting of virus analysts and security experts. This monthly report is published by ASEC and focuses on the most significant security threats and latest security technologies to guard against such threats. For further details, please visit AhnLab, Inc.’s homepage (www. ahnlab.com). SECURITY TREND OF August 2016 Table of Contents 1 01 Malware Statistics 4 02 Web Security Statistics 6 SECURITY STATISTICS 03 Mobile Malware Statistics 7 Ransomware Disguised as PokemonGo to Catch 10 2 Users SECURITY ISSUE Locky Ransomware Disguised as .DLL File 13 3 Appears IN-DEPTH ANALYSIS ASEC REPORT 80 | Security Trend 2 1 SECURITY STATISTICS 01 Malware Statistics 02 Web Security Statistics 03 Mobile Malware Statistics ASEC REPORT 80 | Security Trend SECURITY STATISTICS 01 Malware Statistics According to the ASEC (AhnLab Security Emergency Response Center), 8,793,413 malware were detected in August 2016. The number of detected malware decreased by 955,541 from 9,748,954 detected in the previous month as shown in Figure 1-1. A total of 4,986,496 malware samples were collected in August. 11,000,000 10,000,000 10,467,643 9,748,954 9,000,000 8,793,413 8,000,000 7,000,000 6,000,000 5,000,000 4,000,000 3,000,000 2,000,000 1,000,000 Detected Samples 3,022,206 6,121,096 4,986,496 Collected Samples June July August [Figure 1-1] Malware Trend * “Detected Samples” refers to the number of malware detected by AhnLab products deployed by our customers. -
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. -
Android Malware Category and Family Detection and Identification Using Machine Learning
Android Malware Category and Family Detection and Identification using Machine Learning Ahmed Hashem El Fiky1*, Ayman El Shenawy1, 2, Mohamed Ashraf Madkour1 1 Systems and Computer Engineering Dept., Faculty of Engineering, Al-Azhar University, Cairo, Egypt. 1 Systems and Computer Engineering Dept., Faculty of Engineering, Al-Azhar University, Cairo, Egypt. 2 Software Engineering and Information Technology, Faculty of Engineering and Technology, Egyptian Chinese University, Cairo, Egypt. [email protected] [email protected] [email protected] Abstract: Android malware is one of the most dangerous threats on the internet, and it's been on the rise for several years. Despite significant efforts in detecting and classifying android malware from innocuous android applications, there is still a long way to go. As a result, there is a need to provide a basic understanding of the behavior displayed by the most common Android malware categories and families. Each Android malware family and category has a distinct objective. As a result, it has impacted every corporate area, including healthcare, banking, transportation, government, and e-commerce. In this paper, we presented two machine- learning approaches for Dynamic Analysis of Android Malware: one for detecting and identifying Android Malware Categories and the other for detecting and identifying Android Malware Families, which was accomplished by analyzing a massive malware dataset with 14 prominent malware categories and 180 prominent malware families of CCCS-CIC- AndMal2020 dataset on Dynamic Layers. Our approach achieves in Android Malware Category detection more than 96 % accurate and achieves in Android Malware Family detection more than 99% accurate. Our approach provides a method for high-accuracy Dynamic Analysis of Android Malware while also shortening the time required to analyze smartphone malware. -
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 .