Despite decades of contributions to the theoretical foundations of parsing and the many tools available to aid in parser development, many security attacks in the wild still exploit parsers. The issues are myriad—flaws in memory management in contexts lacking memory safety, flaws in syntactic or semantic validation of input, and misinterpretation of hundred-page-plus standards documents. It remains challenging to build and maintain parsers for common, mature data formats. In response to these challenges, we present Daedalus, a new domain-specific language (DSL) and toolchain for writing safe parsers. Daedalus is built around functional-style parser combinators, which suit the rich data dependencies often found in complex data formats. It adds domain-specific constructs for stream manipulation, allowing the natural expression of parsing noncontiguous formats. Balancing between expressivity and domain-specific constructs lends Daedalus specifications simplicity and leaves them amenable to analysis. As a stand-alone DSL, Daedalus is able to generate safe parsers in multiple languages, currently C++ and Haskell. We have implemented 20 data formats with Daedalus, including two large, complex formats—PDF and NITF–and our evaluation shows that Daedalus parsers are concise and performant. Our experience with PDF forms our largest case study. We worked with the PDF Association to build a reference implementation, which was subject to a red-teaming exercise along with a number of other PDF parsers and was the only parser to be found free of defects.

When runtime verification is used to monitor safety-critical systems, it is essential that monitoring code behaves correctly. The Copilot runtime verification framework pursues this goal by automatically generating C monitor programs from a high-level DSL embedded in Haskell. In safety-critical domains, every piece of deployed code must be accompanied by an assurance argument that is convincing to human auditors. However, it is difficult for auditors to determine with confidence that a compiled monitor cannot crash and implements the behavior required by the Copilot semantics. In this paper we describe CopilotVerifier, which runs alongside the Copilot compiler, generating a proof of correctness for the compiled output. The proof establishes that a given Copilot monitor and its compiled form produce equivalent outputs on equivalent inputs, and that they either crash in identical circumstances or cannot crash. The proof takes the form of a bisimulation broken down into a set of verification conditions. We leverage two pieces of SMT-backed technology: the Crucible symbolic execution library for LLVM and the What4 solver interface library. Our results demonstrate that dramatically increased compiler assurance can be achieved at moderate cost by building on existing tools. This paves the way to our ultimate goal of generating formal assurance arguments that are convincing to human auditors.

Abstract We have completed machine-assisted proofs of two highly-optimized cryptographic primitives, AES-256-GCM and SHA-384. We have verified that the implementations of these primitives, written in a mix of C and x86 assembly, are memory safe and functionally correct, by which we mean input-output equivalent to their algorithmic specifications. Our proofs were completed using SAW, a bounded cryptographic verification tool which we have extended to handle embedded x86. The code we have verified comes from AWS LibCrypto. This code is identical to BoringSSL and very similar to OpenSSL, from which it ultimately derives. We believe we are the first to formally verify these implementations, which protect the security of nearly everybody on the internet.

A valid compiler optimisation transforms a block in a program without introducing new observable behaviours to the program as a whole. Deciding which optimisations are valid can be difficult, and depends closely on the semantic model of the programming language. Axiomatic relaxed models, such as C++11, present particular challenges for determining validity, because such models allow subtle effects of a block transformation to be observed by the rest of the program. In this paper we present a denotational theory that captures optimisation validity on an axiomatic model corresponding to a fragment of C++11. Our theory allows verifying an optimisation compositionally, by considering only the block it transforms instead of the whole program. Using this property, we realise the theory in the first push-button tool that can verify real-world optimisations under an axiomatic memory model.

Synchronization constructs lie at the heart of any reliable concurrent program. Many such constructs are standard (e.g., locks, queues, stacks, and hash-tables). However, many concurrent applications require custom synchronization constructs with special-purpose behavior. These constructs present a significant challenge for verification. Like standard constructs, they rely on subtle racy behavior, but unlike standard constructs, they may not have well-understood abstract interfaces. As they are custom built, such constructs are also far more likely to be unreliable. This article examines the formal specification and verification of custom synchronization constructs. Our target is a library of channels used in automated parallelization to enforce sequential behavior between program statements. Our high-level specification captures the conditions necessary for correct execution; these conditions reflect program dependencies necessary to ensure sequential behavior. We connect the high-level specification with the low-level library implementation to prove that a client’s requirements are satisfied. Significantly, we can reason about program and library correctness without breaking abstraction boundaries. To achieve this, we use a program logic called iCAP (impredicative Concurrent Abstract Predicates) based on separation logic. iCAP supports both high-level abstraction and low-level reasoning about races. We use this to show that our high-level channel specification abstracts three different, increasingly complex low-level implementations of the library. iCAP’s support for higher-order reasoning lets us prove that sequential dependencies are respected, while iCAP’s next-generation semantic model lets us avoid ugly problems with cyclic dependencies.

Concurrent data-structures, such as stacks, queues, and deques, often implicitly enforce a total order over elements in their underlying memory layout. However, much of this order is unnecessary: linearizability only requires that elements are ordered if the insert methods ran in sequence. We propose a new approach which uses timestamping to avoid unnecessary ordering. Pairs of elements can be left unordered if their associated insert operations ran concurrently, and order imposed as necessary at the eventual removal.

When constructing complex concurrent systems, abstraction is vital: programmers should be able to reason about concurrent libraries in terms of abstract specifications that hide the implementation details. Relaxed memory models present substantial challenges in this respect, as libraries need not provide sequentially consistent abstractions: to avoid unnecessary synchronisation, they may allow clients to observe relaxed memory effects, and library specifications must capture these.

We present an analysis which takes as its input a sequential program, augmented with annotations indicating potential parallelization opportunities, and a sequential proof, written in separation logic, and produces a correctly synchronized parallelized program and proof of that program. Unlike previous work, ours is not a simple independence analysis that admits parallelization only when threads do not interfere; rather, we insert synchronization to preserve dependencies in the sequential program that might be violated by a naïve translation. Separation logic allows us to parallelize fine-grained patterns of resource usage, moving beyond straightforward points-to analysis. The sequential proof need only represent shape properties, meaning we can handle complex algorithms without verifying every aspect of their behavior. Our analysis works by using the sequential proof to discover dependencies between different parts of the program. It leverages these discovered dependencies to guide the insertion of synchronization primitives into the parallelized program, and to ensure that the resulting parallelized program satisfies the same specification as the original sequential program, and exhibits the same sequential behavior. Our analysis is built using frame inference and abduction, two techniques supported by an increasing number of separation logic tools.

We present an analysis which takes as its input a sequential program, augmented with annotations indicating potential parallelization opportunities, and a sequential proof, written in separation logic, and produces a correctly-synchronized parallelized program and proof of that program. Unlike previous work, ours is not an independence analysis; we insert synchronization constructs to preserve relevant dependencies found in the sequential program that may otherwise be violated by a naive translation. Separation logic allows us to parallelize fine-grained patterns of resource-usage, moving beyond straightforward points-to analysis. Our analysis works by using the sequential proof to discover dependencies between different parts of the program. It leverages these discovered dependencies to guide the insertion of synchronization primitives into the parallelized program, and to ensure that the resulting parallelized program satisfies the same specification as the original sequential program, and exhibits the same sequential behaviour. Our analysis is built using frame inference and abduction, two techniques supported by an increasing number of separation logic tools.

Asynchronous memory operations provide a means for coping with the memory wall problem in multicore processors, and are available in many platforms and languages, e.g., the Cell Broadband Engine, CUDA and OpenCL. Reasoning about the correct usage of such operations involves complex analysis of memory accesses to check for races. We present a method and tool for proving memory-safety and race-freedom of multicore programs that use asynchronous memory operations. Our approach uses separation logic with permissions, and our tool automates this method, targeting a C-like core language. We describe our solutions to several challenges that arose in the course of this research. These include: syntactic reasoning about permissions and arrays, integration of numerical abstract domains, and utilization of an SMT solver. We demonstrate the feasibility of our approach experimentally by checking absence of DMA races on a set of programs drawn from the IBM Cell SDK.

Indexes are ubiquitous. Examples include associative arrays, dictionaries, maps and hashes used in applications such as databases, file systems and dynamic languages. Abstractly, a sequential index can be viewed as a partial function from keys to values. Values can be queried by their keys, and the index can be mutated by adding or removing mappings. Whilst appealingly simple, this abstract specification is insufficient for reasoning about indexes accessed concurrently. We present an abstract specification for concurrent indexes. We verify several representative concurrent client applications using our specification, demonstrating that clients can reason abstractly without having to consider specific underlying implementations. Our specification would, however, mean nothing if it were not satisfied by standard implementations of concurrent indexes. We verify that our specification is satisfied by algorithms based on linked lists, hash tables and B-Link trees. The complexity of these algorithms, in particular the B-Link tree algorithm, can be completely hidden from the client's view by our abstract specification.

Weaving a concurrency control protocol into a program is difficult and error-prone. One way to alleviate this burden is deterministic parallelism. In this well-studied approach to parallelisation, a sequential program is annotated with sections that can execute concurrently, with automatically injected control constructs used to ensure observable behaviour consistent with the original program.

We present a work-in-progress proof system and tool, based on separation logic, for analysing memory safety of multicore programs that use asynchronous memory operations. Categories and Subject Descriptors F.3.1 [Logics and Meanings

jStar is a tool for automatically verifying Java programs. It uses separation logic to support abstract reasoning about object specifications. jStar can verify a number of challenging design patterns, including Subject/Observer, Visitor, Factory and Pooling. However, to use jStar one has to deal with a family of command-line tools that expect specifications in separate files and diagnose the errors by inspecting the text output from these tools.