探索macOS应用生态中的隐私泄露与数据披露违规问题
Exploring Privacy Leakage and Data Disclosure Violations in the MacOS Application Ecosystem
AI总结：
本文通过NutriScan框架分析1000个macOS应用，发现多数应用存在数据访问未披露、外泄等隐私违规问题，揭示了桌面应用的隐私风险并提出缓解措施。
AI中文摘要：
科技公司系统性且过度的数据收集实践，已使得在线隐私成为一种必需品和备受追捧的商品。不过，尽管网页、移动和物联网生态系统的隐私风险已得到广泛研究，桌面环境却在很大程度上被忽视。随着桌面应用持续被广泛使用，它们仍是用户隐私领域一个关键却未被充分研究的维度。在本文中，我们填补这一空白，开展了据我们所知首个针对macOS生态系统中用于规范和披露数据收集与共享实践的机制的综合性研究。我们采用以应用开发为中心的视角，阐明了介导应用数据访问的各类macOS机制之间的交互作用。基于我们的发现，我们开发了NutriScan这一分析框架，它结合了静态和动态分析技术，以形成macOS应用数据实践与披露的综合视图。我们使用该系统对1000个macOS应用进行动态分析，发现其中85%的应用在访问用户数据API时未对此进行披露；49.7%的应用还会将数据外泄给广告实体和托管提供商，其中12.5%的应用在这样做时未进行相应披露。我们发现，在线跟踪器正利用桌面应用来丰富用户画像和设备指纹，从而为在线跟踪生态系统的真实范围提供了新的视角。我们的分析揭示了macOS应用生态系统如何由具有不同数据抽象的不相交机制构成，这既增加了开发者的复杂性，也为未披露的侵犯隐私行为提供了便利。因此，我们提出了一系列缓解措施，旨在简化开发者的数据披露流程并改进苹果的应用审核流程。
英文摘要：
The systematic and excessive data collection practices of tech companies have rendered online privacy both a necessity and a sought-after commodity. However, while the privacy risks of the web, mobile, and IoT ecosystems have been extensively examined, desktop environments have been largely overlooked. As desktop apps continue to be widely used, they remain a critical yet understudied dimension of user privacy. In this paper, we address this gap by presenting the first, to our knowledge, comprehensive study of the mechanisms designed to regulate and disclose data collection and sharing practices in the macOS ecosystem. We adopt an app-development-centric view, and shed light on the interactions between the various macOS mechanisms that mediate apps' data access. Driven by our findings, we develop NutriScan, an analysis framework that incorporates both static and dynamic analysis techniques to create a consolidated view of macOS apps' data practices and disclosures. We use our system to dynamically analyze 1K macOS apps, and find that 85% of them access user-data APIs without disclosing it. 49.7% also exfiltrate data to advertising entities and hosting providers, 12.5% of which do so without a corresponding disclosure. We find that desktop apps are being leveraged by online trackers to enrich user profiles and device fingerprints, thus shedding new light on the true scope of the online tracking ecosystem. Our analysis reveals how the macOS app ecosystem is comprised of disjoint mechanisms with divergent data abstractions, thus increasing complexity for developers while also facilitating undisclosed privacy-invasive practices. Accordingly, we propose a series of mitigations that aim to both streamline the data disclosure process for developers and improve Apple's app vetting process.
