Offline finding (OF) protocols---such as Apple's Find My, Google's Find Hub, Samsung’s SmartThingsFind, and Tile---enable hundreds of millions of users to track their belongings via Bluetooth-based tracker tags. However, their scale and tracking capabilities give rise to privacy risks for tag owners and bystanders, as well as safety risks for victims of tag-facilitated stalking. In response, academics and practitioners have suggested cryptographic and non-cryptographic mitigations to improve privacy and anti-stalking protections, working to navigate complex and subtle tensions between these goals. The result is a large landscape of privacy goals, threat models, protocol designs, implementations, and analyses. In this work, we systematize the OF protocol landscape. We gather and analyze a corpus of 49 research papers and OF protocol technical specifications, and use it to develop a taxonomy capturing the functionality, security, and privacy goals of OF protocols. We use the taxonomy to guide a focused assessment of the four major OF deployments along with six academic constructions, comparing design choices, consolidating known attacks, and analyzing the designs' trade-offs between privacy, security, abusability, and efficiency. We provide a simple OF protocol that achieves most security goals, and which clarifies the essential cryptographic components underlying OF protocols. We also provide a survey of physical layer attacks and usability issues that undermine protections in practice. Finally, we discuss open problems and potential research directions towards secure, interoperable, and abuse-resistant OF systems.

The recent Digital Markets Act (DMA), a regulation passed by the European Union in 2022, requires messaging applications with large user bases to support interoperable end-to-end encrypted (E2EE) communication. This raises numerous questions about how to adapt cryptographic protocols to this setting in a way that preserves security and privacy. This question is not only limited to the main messaging protocols, but also extends to protocols for abuse mitigation such as the symmetric message franking protocol first proposed by Facebook. The latter uses symmetric cryptography to enable reporting abusive E2EE messages in a way that allows the platform to cryptographically verify the report's veracity.

We explore an emerging threat model for end-to-end (E2E) encrypted applications: an adversary sends chosen messages to a target client, thereby "injecting" adversarial content into the application state. Such state is subsequently encrypted and synchronized to an adversarially-visible storage. By observing the lengths of the resulting cloud-stored cipher-texts, the attacker backs out confidential information.We investigate this injection threat model in the context of state-of-the-art encrypted messaging applications that support E2E encrypted backups. We show proof-of-concept attacks that can recover information about E2E encrypted messages or attachments sent via WhatsApp, assuming the ability to compromise the target user’s Google or Apple account (which gives access to encrypted backups). We also show weaknesses in Signal’s encrypted backup design that would allow injection attacks to infer metadata including a target user’s number of contacts and conversations, should the adversary somehow obtain access to the user’s encrypted Signal backup.While we do not believe our results should be of immediate concern for users of these messaging applications, our results do suggest that more work is needed to build tools that enjoy strong E2E security guarantees.