In real-world scenarios, trusted execution environments (TEEs) frequently host applications that lack the trust of the infrastructure provider, as well as data owners who have specifically outsourced their data for remote processing. We presentTwine, a trusted runtime for running WebAssembly-compiled applications within TEEs, establishing a two-way sandbox.Twineleverages memory safety guarantees of WebAssembly (Wasm) and abstracts the complexity of TEEs, empowering the execution of legacy and language-agnostic applications. It extends the standard WebAssembly system interface (WASI), providing controlled OS services, focusing on I/O. Additionally, through built-in TEE mechanisms,Twinedelivers attestation capabilities to ensure the integrity of the runtime and the OS services supplied to the application. We evaluate its performance using general-purpose benchmarks and real-world applications, showing it compares on par with state-of-the-art solutions. A case study involving fintech companyCredorareveals thatTwinecan be deployed in production with reasonable performance trade-offs, ranging from a 0.7× slowdown to a 1.17× speedup compared to native run time. Finally, we identify performance improvement through library optimisation, showcasing one such adjustment that leads up to$4.1\times$speedup.Twineis open-source and has been upstreamed into the original Wasm runtime, WAMR.

The ideal TEE service model foresees that data owners load their TEE software in an untrusted platform where the specific processing of the business application can take place inside an enclave, shielded against privileged attackers. In this situation, the data owner needs to trust the TEE hardware vendor only. However, it is very common that the enclave software is offered by a third-party that does not share its source code. Therefore, the service provider must be trusted as well. This is not acceptable when privacy requirements are stringent such as in the fintech ecosystem. In this paper, we propose PRIVATON, an approach based on a dual sandbox strategy leveraging TEE technologies with an embedded WebAssembly sandboxed run-time to compute privacy preserving computations modelled as finite state automatons with verifiable proofs of computations. With PRIVATON, the data owner will have the guarantee that even a malicious TEE developer will not be able to get access to the sensitive data. An implementation of PRIVATON was evaluated in the case study provided by the Credora company who is playing the role of a distributed and privacy-preserving credit oracle in the ecosystem of cryptocurrencies trading.