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The fast-paced development and deployment of private messaging applications demands mechanisms to protect against the concomitant potential for abuse. While widely used end-to-end encrypted (E2EE) messaging systems have deployed mechanisms for users to verifiably report abusive messages without compromising the privacy of unreported messages, abuse reporting schemes for systems that additionally protect message metadata are still in their infancy. Existing solutions either focus on a relatively small portion of the design space or incur much higher communication and computation costs than their E2EE brethren. This paper introduces new abuse reporting mechanisms that work for any private messaging system based on onion encryption. This includes low-latency systems that employ heuristic or opportunistic mixing of user traffic, as well as schemes based on mixnets. Along the way, we show that design decisions and abstractions that are well-suited to the E2EE setting may actually impede security and performance improvements in the metadata-hiding setting. We also explore stronger threat models for abuse reporting and moderation not explored in prior work, showing where prior work falls short and how to strengthen both our scheme and others'—including deployed E2EE messaging platforms—to achieve higher levels of security. We implement a prototype of our scheme and find that it outperforms the best known solutions in this setting by well over an order of magnitude for each step of the message delivery and reporting process, with overheads almost matching those of message franking techniques used by E2EE encrypted messaging apps today. 

We present SEIF, an exploratory methodology for information flow verification based on symbolic execution. SEIF begins with a statically built overapproximation of the information flow through a design and uses guided symbolic execution to provide a more precise picture of how information flows from a given set of security critical signals. SEIF can recognize and eliminate non-flows with high precision and for the true flows can find the corresponding paths through the design state with high coverage. We evaluate SEIF on two open-source CPUs, an AES core, and the AKER access control module. SEIF can be used to find counterexamples to information flow properties, and also to explore all flows originating from a source signal of interest. SEIF accounts for 86–90% of statically identified possible flows in three open-source designs. SEIF’s search strategies enable exploring the designs for 10-12 clock cycles in 4-6 seconds on average, demonstrating that this new exploratory style of information flow analysis can be practical.