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Iris-Wasm: Robust and Modular Verification of WebAssembly Programs

2023; Association for Computing Machinery; Volume: 7; Issue: PLDI Linguagem: Inglês

10.1145/3591265

2475-1421

Xiaojia Rao, Aïna Linn Georges, Maxime Legoupil, Conrad Watt, Jean Pichon-Pharabod, Philippa Gardner, Lars Birkedal,

Adversarial Robustness in Machine Learning

WebAssembly makes it possible to run C/C++ applications on the web with near-native performance. A WebAssembly program is expressed as a collection of higher-order ML-like modules, which are composed together through a system of explicit imports and exports using a host language, enabling a form of higher- order modular programming. We present Iris-Wasm, a mechanized higher-order separation logic building on a specification of Wasm 1.0 mechanized in Coq and the Iris framework. Using Iris-Wasm, we are able to specify and verify individual modules separately, and then compose them modularly in a simple host language featuring the core operations of the WebAssembly JavaScript Interface. Building on Iris-Wasm, we develop a logical relation that enforces robust safety: unknown, adversarial code can only affect other modules through the functions that they explicitly export. Together, the program logic and the logical relation allow us to formally verify functional correctness of WebAssembly programs, even when they invoke and are invoked by unknown code, thereby demonstrating that WebAssembly enforces strong isolation between modules.