The Parcel mechanism is a key component in inter-process communication in Android. However, due to the lack of security considerations, incorrect implementation of the Parcel mechanism can lead to security vulnerabilities. In the past decade, these security vulnerabilities have impacted numerous Android users. In this paper, we identify two major security issues of the Parcel mechanism. First, the reading and writing components are implemented inconsistently in some Parcelable classes, compromising data integrity. Second, malformed Parcels introduce the potential for Denial-of-Service (DoS) attacks on critical apps. We then describe two types of attacks to exploit these two issues: a privilege escalation attack and the Malformed Parcel DoS attack, the latter of which renders phones unusable and prevents users from accessing critical services. To understand the scope of our proposed attacks across the entire Android ecosystem, we perform the first large-scale analysis on 324 Android firmware samples and 10,161 Android apps. Among them, we identify 36 unique data mismatch vulnerabilities and 3,858 apps vulnerable to the DoS attack. We responsibly disclosed our findings to vendors, and 10 of them have been confirmed. Finally, we propose mitigations against the attacks.

In recent years, there has been a surge in the popularity of mobile super apps, which consolidate a variety of services, including messaging, ride-hailing, and e-commerce, into a single application, eliminating the need to switch between different apps. Originally tailored for mobile usage, super apps like WeChat and WeCom have expanded their reach to desktop platforms, including Windows. However, different operating systems have different threat models (e.g., Windows can directly grant users with root privilege but Android and iOS do not). Therefore, the single super app (including both its host app and miniapps) can face completely different threats in different platforms. In this paper, we systematically study the attacks caused by the discrepancies from different platforms. Specifically, we show that there are at least two classes of attacks, dubbed RootFree attacks, against mobile super apps: layer below that attacks the super apps from privileged software, and layer up that attacks the super apps from the internal malicious miniapps. We have disclosed our attacks and the corresponding vulnerabilities to the host app vendor, and received bug bounties. These vulnerabilities all are ranked as high severity vulnerabilities, and some of them have already been patched.

Mobile applications, particularly those from social media platforms such as WeChat and TikTok, are evolving into "super apps" that offer a wide range of services such as instant messaging and media sharing, e-commerce, e-learning, and e-government. These super apps often provide APIs for developers to create "miniapps" that run within the super app. These APIs should have been thoroughly scrutinized for security. Unfortunately, we find that many of them are undocumented and unsecured, potentially allowing miniapps to bypass restrictions and gain higher privileged access. To systematically identify these hidden APIs before they are exploited by attackers, we have developed a tool APIScope with both static analysis and dynamic analysis, where static analysis is used to recognize hidden undocumented APIs, and dynamic analysis is used to confirm whether the identified APIs can be invoked by an unprivileged 3rd-party miniapps. We have applied APIScope to five popular super apps (i.e., WeChat, WeCom, Baidu, QQ, and Tiktok) and found that all of them contain hidden APIs, many of which can be exploited due to missing security checks. We have also quantified the hidden APIs that may have security implications by verifying if they have access to resources protected by Android permissions. Furthermore, we demonstrate the potential security hazards by presenting various attack scenarios, including unauthorized access to any web pages, downloading and installing malicious software, and stealing sensitive information. We have reported our findings to the relevant vendors, some of whom have patched the vulnerabilities and rewarded us with bug bounties.

Mini-programs, which are programs running inside mobile super apps such as WeChat, often have access to privacy-sensitive information, such as location data and phone numbers, through APUs provided by the super apps. This access poses a risk of privacy sensitive data leaks, either accidentally from carelessly programmed mini-programs or intentionally from malicious ones. To address this concern, it is crucial to track the flow of sensitive data in mini-programs for either human analysis or automated tools. Although existing taint analysis techniques have been widely studied, they face unique challenges in tracking sensitive data flows in mini-programs, such as cross-language, cross-page, and cross-mini-program data flows. This paper presents a novel framework, Taintmini, which addresses these challenges by using a novel universal data flow graph approach that captures data flows within and across mini-programs. We have evaluated Taintminiwith 238,866 mini-programs and detect 27,184 that contain sensitive data flows. We have also applied Taintminito detect privacy leakage colluding mini-programs and identify 455 such programs from them that clearly violate privacy policy.