Human Factors in Secure Software Development

While security research has made significant progress in the development of theoretically secure methods, software and algorithms, software still comes with many possible exploits, many of those using the human factor. The human factor is often called ``the weakest link'' in software security. To solve this, human factors research in security and privacy focus on the users of technology and consider their security needs. The research then asks how technology can serve users while minimizing risks and empowering them to retain control over their own data. However, these concepts have to be implemented by developers whose security errors may proliferate to all of their software's users. For example, software that stores data in an insecure way, does not secure network traffic correctly, or otherwise fails to adhere to secure programming best practices puts all of the software's users at risk. It is therefore critical that software developers implement security correctly. However, in addition to security rarely being a primary concern while producing software, developers may also not have extensive awareness, knowledge, training or experience in secure development. A lack of focus on usability in libraries, documentation, and tools that they have to use for security-critical components may exacerbate the problem by blowing up the investment of time and effort needed to "get security right". This dissertation's focus is how to support developers throughout the process of implementing software securely. This research aims to understand developers' use of resources, their mindsets as they develop, and how their background impacts code security outcomes. Qualitative, quantitative and mixed methods were employed online and in the laboratory, and large scale datasets were analyzed to conduct this research. This research found that the information sources developers use can contribute to code (in)security: copying and pasting code from online forums leads to achieving functional code quickly compared to using official documentation resources, but may introduce vulnerable code. We also compared the usability of cryptographic APIs, finding that poor usability, unsafe (possibly obsolete) defaults and unhelpful documentation also lead to insecure code. On the flip side, well-thought out documentation and abstraction levels can help improve an API's usability and may contribute to secure API usage. We found that developer experience can contribute to better security outcomes, and that studying students in lieu of professional developers can produce meaningful insights into developers' experiences with secure programming. We found that there is a multitude of online secure development advice, but that these advice sources are incomplete and may be insufficient for developers to retrieve help, which may cause them to choose un-vetted and potentially insecure resources. This dissertation supports that (a) secure development is subject to human factor challenges and (b) security can be improved by addressing these challenges and supporting developers. The work presented in this dissertation has been seminal in establishing human factors in secure development research within the security and privacy community and has advanced the dialogue about the rigorous use of empirical methods in security and privacy research. In these research projects, we repeatedly found that usability issues of security and privacy mechanisms, development practices, and operation routines are what leads to the majority of security and privacy failures that affect millions of end users

ATTACKS AND COUNTERMEASURES FOR WEBVIEW ON MOBILE SYSTEMS

ABSTRACT All the mainstream mobile operating systems provide a web container, called ``WebView\u27\u27. This Web-based interface can be included as part of the mobile application to retrieve and display web contents from remote servers. WebView not only provides the same functionalities as web browser, more importantly, it enables rich interactions between mobile apps and webpages loaded inside WebView. Through its APIs, WebView enables the two-way interaction. However, the design of WebView changes the landscape of the Web, especially from the security perspective. This dissertation conducts a comprehensive and systematic study of WebView\u27s impact on web security, with a particular focus on identifying its fundamental causes. This dissertation discovers multiple attacks on WebView, and proposes new protection models to enhance the security of WebView. The design principles of these models are also described as well as the prototype implementation in Android platform. Evaluations are used to demonstrate the effectiveness and performance of these protection models

Mitigating security and privacy threats from untrusted application components on Android

Aufgrund von Androids datenzentrierter und Open-Source Natur sowie von fehlerhaften/bösartigen Apps durch das lockere Marktzulassungsverfahren, ist die Privatsphäre von Benutzern besonders gefährdet. Diese Dissertation präsentiert eine Reihe von Forschungsarbeiten, die die Bedrohung der Sicherheit/Privatsphäre durch nicht vertrauenswürdige Appkomponenten mindern. Die erste Arbeit stellt eine Compiler-basierte Kompartmentalisierungslösung vor, die Privilegientrennung nutzt, um eine starke Barriere zwischen der Host-App und Bibliothekskomponenten zu etablieren, und somit sensible Daten vor der Kompromittierung durch neugierige/bösartige Werbe-Bibliotheken schützt. Für fehleranfällige Bibliotheken von Drittanbietern implementieren wir in der zweiten Arbeit ein auf API-Kompatibilität basierendes Bibliothek-Update-Framework, das veraltete Bibliotheken durch Drop-Ins aktualisiert, um das durch Bibliotheken verursachte Zeitfenster der Verwundbarkeit zu minimieren. Die neueste Arbeit untersucht die missbräuchliche Nutzung von privilegierten Accessibility(a11y)-Funktionen in bösartigen Apps. Wir zeigen ein datenschutzfreundliches a11y-Framework, das die a11y-Logik wie eine Pipeline behandelt, die aus mehreren Modulen besteht, die in verschiedenen Sandboxen laufen. Weiterhin erzwingen wir eine Flusskontrolle über die Kommunikation zwischen den Modulen, wodurch die Angriffsfläche für den Missbrauch von a11y-APIs verringert wird, während die Vorteile von a11y erhalten bleiben.While Android’s data-intensive and open-source nature, combined with its less-than-strict market approval process, has allowed the installation of flawed and even malicious apps, its coarse-grained security model and update bottleneck in the app ecosystem make the platform’s privacy and security situation more worrying. This dissertation introduces a line of works that mitigate privacy and security threats from untrusted app components. The first work presents a compiler-based library compartmentalization solution that utilizes privilege separation to establish a strong trustworthy boundary between the host app and untrusted lib components, thus protecting sensitive user data from being compromised by curious or malicious ad libraries. While for vulnerable third-party libraries, we then build the second work that implements an API-compatibility-based library update framework using drop-in replacements of outdated libraries to minimize the open vulnerability window caused by libraries and we perform multiple dynamic tests and case studies to investigate its feasibility. Our latest work focuses on the misusing of powerful accessibility (a11y) features in untrusted apps. We present a privacy-enhanced a11y framework that treats the a11y logic as a pipeline composed of multiple modules running in different sandboxes. We further enforce flow control over the communication between modules, thus reducing the attack surface from abusing a11y APIs while preserving the a11y benefits

Overcoming Language Dichotomies: Toward Effective Program Comprehension for Mobile App Development

Mobile devices and platforms have become an established target for modern software developers due to performant hardware and a large and growing user base numbering in the billions. Despite their popularity, the software development process for mobile apps comes with a set of unique, domain-specific challenges rooted in program comprehension. Many of these challenges stem from developer difficulties in reasoning about different representations of a program, a phenomenon we define as a "language dichotomy". In this paper, we reflect upon the various language dichotomies that contribute to open problems in program comprehension and development for mobile apps. Furthermore, to help guide the research community towards effective solutions for these problems, we provide a roadmap of directions for future work.Comment: Invited Keynote Paper for the 26th IEEE/ACM International Conference on Program Comprehension (ICPC'18

“And all the pieces matter...” Hybrid Testing Methods for Android App's Privacy Analysis

Smartphones have become inherent to the every day life of billions of people worldwide, and they are used to perform activities such as gaming, interacting with our peers or working. While extremely useful, smartphone apps also have drawbacks, as they can affect the security and privacy of users. Android devices hold a lot of personal data from users, including their social circles (e.g., contacts), usage patterns (e.g., app usage and visited websites) and their physical location. Like in most software products, Android apps often include third-party code (Software Development Kits or SDKs) to include functionality in the app without the need to develop it in-house. Android apps and third-party components embedded in them are often interested in accessing such data, as the online ecosystem is dominated by data-driven business models and revenue streams like advertising. The research community has developed many methods and techniques for analyzing the privacy and security risks of mobile apps, mostly relying on two techniques: static code analysis and dynamic runtime analysis. Static analysis analyzes the code and other resources of an app to detect potential app behaviors. While this makes static analysis easier to scale, it has other drawbacks such as missing app behaviors when developers obfuscate the app’s code to avoid scrutiny. Furthermore, since static analysis only shows potential app behavior, this needs to be confirmed as it can also report false positives due to dead or legacy code. Dynamic analysis analyzes the apps at runtime to provide actual evidence of their behavior. However, these techniques are harder to scale as they need to be run on an instrumented device to collect runtime data. Similarly, there is a need to stimulate the app, simulating real inputs to examine as many code-paths as possible. While there are some automatic techniques to generate synthetic inputs, they have been shown to be insufficient. In this thesis, we explore the benefits of combining static and dynamic analysis techniques to complement each other and reduce their limitations. While most previous work has often relied on using these techniques in isolation, we combine their strengths in different and novel ways that allow us to further study different privacy issues on the Android ecosystem. Namely, we demonstrate the potential of combining these complementary methods to study three inter-related issues: • A regulatory analysis of parental control apps. We use a novel methodology that relies on easy-to-scale static analysis techniques to pin-point potential privacy issues and violations of current legislation by Android apps and their embedded SDKs. We rely on the results from our static analysis to inform the way in which we manually exercise the apps, maximizing our ability to obtain real evidence of these misbehaviors. We study 46 publicly available apps and find instances of data collection and sharing without consent and insecure network transmissions containing personal data. We also see that these apps fail to properly disclose these practices in their privacy policy. • A security analysis of the unauthorized access to permission-protected data without user consent. We use a novel technique that combines the strengths of static and dynamic analysis, by first comparing the data sent by applications at runtime with the permissions granted to each app in order to find instances of potential unauthorized access to permission protected data. Once we have discovered the apps that are accessing personal data without permission, we statically analyze their code in order to discover covert- and side-channels used by apps and SDKs to circumvent the permission system. This methodology allows us to discover apps using the MAC address as a surrogate for location data, two SDKs using the external storage as a covert-channel to share unique identifiers and an app using picture metadata to gain unauthorized access to location data. • A novel SDK detection methodology that relies on obtaining signals observed both in the app’s code and static resources and during its runtime behavior. Then, we rely on a tree structure together with a confidence based system to accurately detect SDK presence without the need of any a priory knowledge and with the ability to discern whether a given SDK is part of legacy or dead code. We prove that this novel methodology can discover third-party SDKs with more accuracy than state-of-the-art tools both on a set of purpose-built ground-truth apps and on a dataset of 5k publicly available apps. With these three case studies, we are able to highlight the benefits of combining static and dynamic analysis techniques for the study of the privacy and security guarantees and risks of Android apps and third-party SDKs. The use of these techniques in isolation would not have allowed us to deeply investigate these privacy issues, as we would lack the ability to provide real evidence of potential breaches of legislation, to pin-point the specific way in which apps are leveraging cover and side channels to break Android’s permission system or we would be unable to adapt to an ever-changing ecosystem of Android third-party companies.The works presented in this thesis were partially funded within the framework of the following projects and grants: • European Union’s Horizon 2020 Innovation Action program (Grant Agreement No. 786741, SMOOTH Project and Grant Agreement No. 101021377, TRUST AWARE Project). • Spanish Government ODIO NºPID2019-111429RB-C21/PID2019-111429RBC22. • The Spanish Data Protection Agency (AEPD) • AppCensus Inc.This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Srdjan Matic.- Secretario: Guillermo Suárez-Tangil.- Vocal: Ben Stoc

Implications of smartphone user privacy leakage from the advertiser’s perspective

Many smartphone apps routinely gather various private user data and send them to advertisers. Despite recent study on protection mechanisms and analysis on apps’ behavior, the understanding of the consequences of such privacy losses remains limited. In this paper, we investigate how much an advertiser can infer about users’ social and community relationships. After one month’s user study involving about 190 most popular Android apps, we find that an advertiser can infer 90% of the social relationships. We further propose a privacy leakage inference framework and use real mobility traces and Foursquare data to quantify the consequences of privacy leakage. We find that achieving 90% inference accuracy of the social and community relationships requires merely 3 weeks’ user data. Finally, we present a real-time privacy leakage visualization tool that captures and displays the spatial–temporal characteristics of the leakages. The discoveries underscore the importance of early adoption of privacy protection mechanisms

SYSTEMATIC DISCOVERY OF ANDROID CUSTOMIZATION HAZARDS

The open nature of Android ecosystem has naturally laid the foundation for a highly fragmented operating system. In fact, the official AOSP versions have been aggressively customized into thousands of system images by everyone in the customization chain, such as device manufacturers, vendors, carriers, etc. If not well thought-out, the customization process could result in serious security problems. This dissertation performs a systematic investigation of Android customization’ inconsistencies with regards to security aspects at various Android layers. It brings to light new vulnerabilities, never investigated before, caused by the under-regulated and complex Android customization. It first describes a novel vulnerability Hare and proves that it is security critical and extensive affecting devices from major vendors. A new tool is proposed to detect the Hare problem and to protect affected devices. This dissertation further discovers security configuration changes through a systematic differential analysis among custom devices from different vendors and demonstrates that they could lead to severe vulnerabilities if introduced unintentionally

Enhancing users\u27 experiences with mobile app stores: What do users see? What should they see?

Using mobile applications is one of the daily habits for most smartphone users. In order to select applications, individuals need to explore the apps stores. Apps’ exploration is disturbed by the way of illustrating the applications’ information. This dissertation consists of three studies that aimed to: 1) Investigate the users’ experience with the apps’ stores; 2) Collect the users’ needs and requirements in order to have a better experience with the interface of apps’ stores; 3) Propose and evaluate a new interface design for the apps’ stores. Different types of data collection methods were administered while proceeding with the phases of this dissertation. The first study was an exploratory study, which administered an online survey, where we had102 respondents. The second study, aimed to collect the design requirements, and we interviewed 16 individuals. The third study was the interface evaluation, where we also had 35 participants. Our results showed multiple factors that affect users’ experience while discovering applications on the apps’ store. Our findings suggested that the current interface design of apps’ stores needs revisions to help users to be aware of apps’ emerging features and issues. Moreover, we found that visual cues that illustrate apps’ information would be more effective to help users perceive specific information about apps. Furthermore, visual indicators would enhance users’ knowledge regarding some of the apps’ concerns. At the end of this research, we evaluated a proposed interface design that integrates the previous design recommendations. The evaluation results illustrated positive outputs in terms of users’ satisfaction and task-completion rate. The findings indicated that participants were delighted to experience the new way of interaction with the interface of apps’ store. We anticipate that users’ experience and their awareness towards the apps issue would be improved if apps’ stores considered adopting the proposed design concept