We present a security analysis of the messaging service known as LINE, a popular platform used daily by millions of users in Southeast Asia - most notably Japan, Taiwan, Thailand, and Indonesia. More specifically, we focus on its underlying custom end-to-end encryption (E2EE) protocol, known as Letter Sealing v2. Our findings show that Letter Sealing allows a TLS Machine-in-the-Middle attacker or malicious server to violate integrity, authenticity, and confidentiality of communications. The stateless design of the protocol allows message replay, reordering, and blocking attacks without the user being notified. The lack of origin authentication facilitates impersonation attacks, in which the authorship of messages in one-to-one or group chats can be forged by malicious users colluding with the adversary. Lastly, stickers and URL previews present a notable leakage of plaintext, which leads to a violation of confidentiality. To verify the correctness of our findings, we mounted a Machine-in-the-Middle attack on an iOS device, yielding the device's outgoing traffic and the corresponding server responses. Utilizing this setup, we experimentally verified our attacks against the authentic LINE application and an independent implementation. We discuss our findings in comparison to the state-of-the-art E2EE protocols, and conclude that Letter Sealing does not satisfy the requirements expected from a modern E2EE messaging protocol.

We construct protocols for oblivious pseudorandom functions (OPRFs) based on alternating moduli assumptions in the 'Crypto Dark Matter' paradigm (Boneh et al, TCC 2016). Prior OPRFs based on this type of assumption were only secure against a semi-honest adversary. We show how to obtain maliciously secure protocols, by leveraging new cut-and-choose techniques for generating correlated randomness based on vector oblivious linear evaluation (VOLE), which allow efficient conversions between different moduli in zero-knowledge and secure two-party computation. Compared with the state-of-the-art GOLD OPRF (Yang et al, S&P 2025), our construction has a faster online phase in all settings, as well as overall better efficiency in the small-batch setting. Furthermore, our construction supports obtaining a secret-shared output, and can be extended to handle secretshared inputs. This opens up additional applications in variants of private set intersection and secure database operations.