Send and Pretend: Exploiting Transcript Consistency Issues in End-to-End Encrypted Group Chats

2026-07-29

AI Summary

This study addresses a critical yet overlooked vulnerability in mainstream end-to-end encrypted (E2EE) group messaging systems: the lack of transcript consistency guarantees. Malicious participants can exploit protocol fallbacks, pairwise channels, and other mechanisms to deliver inconsistent messages to different recipients, thereby undermining group consensus without detection. The work presents the first systematic analysis of this issue, introducing a cross-platform attack model that uncovers novel privacy risks such as device fingerprint leakage. Through protocol reverse engineering, message path tracing, and UI behavior testing across real-world E2EE applications, the authors identify multiple inconsistency vectors and demonstrate practical attacks—including vote manipulation, moderation evasion, and social engineering. Finally, they propose lightweight mitigation mechanisms and user interface warning strategies that significantly enhance transcript consistency in group chats.

Abstract

End-to-end encrypted (E2EE) messaging apps are widely praised for their security and thus also used for sensitive coordination in group chats (e.g., by political decision makers). After Threema and WhatsApp, also Signal and iMessage have recently introduced polls to aid agreement processes in groups. This implicitly sets the expectation that all participants see the same outcome and thus have the same view of the conversation. This property is commonly referred to as transcript consistency (TC). In this work, we demonstrate that today's major E2EE messengers do not guarantee any form of TC for group chats, allowing a malicious group member to selectively omit, reorder, or present altered content to different recipients without triggering warnings in their user interface. We systematically investigate the extent of the problem under a malicious-participant threat model that targets the integrity of the shared transcript, or inconsistent delivery across a user's linked devices. We identify multiple equivocation vectors that range from protocol fallback paths to deliberate use of pairwise delivery channels within groups. We demonstrate concrete exploitation scenarios such as social engineering, evading moderation, and, in particular, rigging polls. Beyond these cross-service design issues, we also uncover implementation-specific behaviors with privacy implications (e.g., device OS fingerprinting). Finally, we contextualize our findings within prior transcript-consistency research and outline practical low-overhead mitigations and UI signaling strategies that can be integrated into state-of-the-art E2EE group protocols.

Problem

• transcript consistency
• end-to-end encryption
• group chat
• message integrity
• equivocation

Innovation

• transcript consistency
• end-to-end encryption
• group messaging
• equivocation attacks
• poll manipulation