Abstract With the explosion in popularity of the Rust programming language, a wealth of tools have recently been developed to analyze, verify, and test Rust programs. Alas, the Rust ecosystem remains relatively young, meaning that every one of these tools has had to re-implement difficult, time-consuming machinery to interface with the Rust compiler and its cargo build system, to hook into the Rust compiler’s internal representation, and to expose an abstract syntax tree (AST) that is suitable for analysis rather than optimized for efficiency. We address this missing building block of the Rust ecosystem, and propose Charon, an analysis framework for Rust. Charon acts as a swiss-army knife for analyzing Rust programs, and deals with all of the tedium above, providing clients with an AST that can serve as the foundation of many analyses. We demonstrate the usefulness of Charon through a series of case studies, ranging from a Rust verification framework (Aeneas), a compiler from Rust to C (Eurydice), and a novel taint-checker for cryptographic code. To drive the point home, we also re-implement a popular existing analysis (Rudra), and show that it can be replicated by leveraging the Charon framework.

The Rust programming language continues to rise in popularity, and as such, warrants the close attention of the programming languages community. In this work, we present a new foundational contribution towards the theoretical understanding of Rust’s semantics. We prove that LLBC, a high-level, borrow-centric model previously proposed for Rust’s semantics and execution, is sound with regards to a low-level pointer-based language à la CompCert. Specifically, we prove the following: that LLBC is a correct view over a traditional model of execution; that LLBC’s symbolic semantics are a correct abstraction of LLBC programs; and that LLBC’s symbolic semantics act as a borrow-checker for LLBC, i.e. that symbolically-checked LLBC programs do not get stuck when executed on a heap-and-addresses model of execution. To prove these results, we introduce a new proof style that considerably simplifies our proofs of simulation, which relies on a notion of hybrid states. Equipped with this reasoning framework, we show that a new addition to LLBC’s symbolic semantics, namely a join operation, preserves the abstraction and borrow-checking properties. This in turn allows us to add support for loops to the Aeneas framework; we show, using a series of examples and case studies, that this unlocks new expressive power for Aeneas.

For all the successes in verifying low-level, efficient, security-critical code, little has been said or studied about the structure, architecture and engineering of such large-scale proof developments. We present the design, implementation and evaluation of a set of language-based techniques that allow the programmer to modularly write and verify code at a high level of abstraction, while retaining control over the compilation process and producing high-quality, zero-overhead, low-level code suitable for integration into mainstream software. We implement our techniques within the F proof assistant, and specifically its shallowly-embedded Low toolchain that compiles to C. Through our evaluation, we establish that our techniques were critical in scaling the popular HACL library past 100,000 lines of verified source code, and brought about significant gains in proof engineer productivity. The exposition of our methodology converges on one final, novel case study: the streaming API, a finicky API that has historically caused many bugs in high-profile software. Using our approach, we manage to capture the streaming semantics in a generic way, and apply it “for free” to over a dozen use-cases. Six of those have made it into the reference implementation of the Python programming language, replacing the previous CVE-ridden code.

The Noise protocol framework defines a succinct notation and execution framework for a large class of 59+ secure channel protocols, some of which are used in popular applications such as WhatsApp and WireGuard. We present a verified implementation of a Noise protocol compiler that takes any Noise protocol, and produces an optimized C implementation with extensive correctness and security guarantees. To this end, we formalize the complete Noise stack in F*, from the low-level cryptographic library to a high-level API. We write our compiler also in F*, prove that it meets our formal specification once and for all, and then specialize it on-demand for any given Noise protocol, relying on a novel technique called hybrid embedding. We thus establish functional correctness, memory safety and a form of side-channel resistance for the generated C code for each Noise protocol. We propagate these guarantees to the high-level API, using defensive dynamic checks to prevent incorrect uses of the protocol. Finally, we formally state and prove the security of our Noise code, by building on a symbolic model of cryptography in F*, and formally link high-level API security goals stated in terms of security levels to low-level cryptographic guarantees. Ours are the first comprehensive verification results for a protocol compiler that targets C code and the first verified implementations of any Noise protocol. We evaluate our framework by generating implementations for all 59 Noise protocols and by comparing the size, performance, and security of our verified code against other (unverified) implementations and prior security analyses of Noise.

We present Aeneas, a new verification toolchain for Rust programs based on a lightweight functional translation. We leverage Rust’s rich region-based type system to eliminate memory reasoning for a large class of Rust programs, as long as they do not rely on interior mutability or unsafe code. Doing so, we relieve the proof engineer of the burden of memory-based reasoning, allowing them to instead focus on functional properties of their code. The first contribution of Aeneas is a new approach to borrows and controlled aliasing. We propose a pure, functional semantics for LLBC, a Low-Level Borrow Calculus that captures a large subset of Rust programs. Our semantics is value-based, meaning there is no notion of memory, addresses or pointer arithmetic. Our semantics is also ownership-centric, meaning that we enforce soundness of borrows via a semantic criterion based on loans rather than through a syntactic type-based lifetime discipline. We claim that our semantics captures the essence of the borrow mechanism rather than its current implementation in the Rust compiler. The second contribution of Aeneas is a translation from LLBC to a pure lambda-calculus. This allows the user to reason about the original Rust program through the theorem prover of their choice, and fulfills our promise of enabling lightweight verification of Rust programs. To deal with the well-known technical difficulty of terminating a borrow, we rely on a novel approach, in which we approximate the borrow graph in the presence of function calls. This in turn allows us to perform the translation using a new technical device called backward functions. We implement our toolchain in a mixture of Rust and OCaml; our chief case study is a low-level, resizing hash table, for which we prove functional correctness, the first such result in Rust. Our evaluation shows significant gains of verification productivity for the programmer. This paper therefore establishes a new point in the design space of Rust verification toolchains, one that aims to verify Rust programs simply, and at scale. Rust goes to great lengths to enforce static control of aliasing; the proof engineer should not waste any time on memory reasoning when so much already comes “for free”!

Abstract We introduce an automatic method for producing stateful ML programs together with proofs of correctness from monadic functions in HOL. Our mechanism supports references, exceptions, and I/O operations, and can generate functions manipulating local state, which can then be encapsulated for use in a pure context. We apply this approach to several non-trivial examples, including the instruction encoder and register allocator of the otherwise pure CakeML compiler, which now benefits from better runtime performance. This development has been carried out in the HOL4 theorem prover.