Afonso Falcão, Andreia Mordido, Vasco T. Vasconcelos
The popularity of smart contracts is on the rise, yet breaches in reliability and security linger. Among the many facets of smart contract reliability, we concentrate on faults rooted in out-of-order interactions with contract endpoints. We propose SmartScribble, a protocol language to describe valid patterns of interaction between users and endpoints. SmartScribble not only ensures correct interactive behaviour but also simplifies smart contract coding. From a protocol description, our compiler generates a smart contract that can then be completed by the programmer with the relevant business logic. The generated contracts rely on finite state machines to control endpoint invocations. As a proof of concept, we target Plutus, the contract programming language for the Cardano blockchain. Preliminary evaluation points to a 75% decrease in the size of the code that developers must write, coupled with an increase of reliability by enforcing the specified patterns of interaction.
Smart contracts hold digital coins worth billions of dollars, their security issues have drawn extensive attention in the past years. Towards smart contract vulnerability detection, conventional methods heavily rely on fixed expert rules, leading to low accuracy and poor scalability. Recent deep learning approaches alleviate this issue but fail to encode useful expert knowledge. In this paper, we explore combining deep learning with expert patterns in an explainable fashion. Specifically, we develop automatic tools to extract expert patterns from the source code. We then cast the code into a semantic graph to extract deep graph features. Thereafter, the global graph feature and local expert patterns are fused to cooperate and approach the final prediction, while yielding their interpretable weights. Experiments are conducted on all available smart contracts with source code in two platforms, Ethereum and VNT Chain. Empirically, our system significantly outperforms state-of-the-art methods. Our code is released.
Context: Decentralized applications on blockchain platforms are realized through smart contracts. However, participants who lack programming knowledge often have difficulties reading the smart contract source codes, which leads to potential security risks and barriers to participation. Objective: Our objective is to translate the smart contract source codes into natural language descriptions to help people better understand, operate, and learn smart contracts. Method: This paper proposes an automated translation tool for Solidity smart contracts, termed SolcTrans, based on an abstract syntax tree and formal grammar. We have investigated 3,000 smart contracts and determined the part of speeches of corresponding blockchain terms. Among them, we further filtered out contract snippets without detailed comments and left 811 snippets to evaluate the translation quality of SolcTrans. Results: Experimental results show that even with a small corpus, SolcTrans can achieve similar performance to the state-of-the-art code comments generation models for other programming languages. In addition, SolcTrans has consistent performance when dealing with code snippets with different lengths and gas consumption. Conclusion: SolcTrans can correctly interpret Solidity codes and automatically convert them into comprehensible English text. We will release our tool and dataset for supporting reproduction and further studies in related fields.
Sota Sato, Ryotaro Banno, Jun Furuse, Kohei Suenaga · 5 authors
A Merkle tree is a data structure for representing a key-value store as a tree. Each node of a Merkle tree is equipped with a hash value computed from those of their descendants. A Merkle tree is often used for representing a state of a blockchain system since it can be used for efficiently auditing the state in a trustless manner. Due to the safety-critical nature of blockchains, ensuring the correctness of their implementation is paramount. We show our formally verified implementation of the core part of Plebeia using F*. Plebeia is a library to manipulate an extension of Merkle trees (called Plebeia trees). It is being implemented as a part of the storage system of the Tezos blockchain system. To this end, we gradually ported Plebeia to F*; the OCaml code extracted from the modules ported to F* is linked with the unverified part of Plebeia. By this gradual porting process, we can obtain a working code from our partially verified implementation of Plebeia; we confirmed that the binary passes all the unit tests of Plebeia. More specifically, we verified the following properties on the implementation of Plebeia: (1) Each tree-manipulating function preserves the invariants on the data structure of a Plebeia tree and satisfies the functional requirements as a nested key-value store; (2) Each function for serializing/deserializing a Plebeia tree to/from the low-level storage is implemented correctly; and (3) The hash function for a Plebeia tree is relatively collision-resistant with respect to the cryptographic safety of the blake2b hash function. During porting Plebeia to F*, we found a bug in an old version of Plebeia, which was overlooked by the tests bundled with the original implementation. To the best of our knowledge, this is the first work that verifies a production-level implementation of a Merkle-tree library by F*.
Christian Bräm, Marco Eilers, Péter Müller, Robin Sierra · 5 authors
Smart contracts are programs that execute inside blockchains such as Ethereum to manipulate digital assets. Since bugs in smart contracts may lead to substantial financial losses, there is considerable interest in formally proving their correctness. However, the specification and verification of smart contracts faces challenges that do not arise in other application domains. Smart contracts frequently interact with unverified, potentially adversarial outside code, which substantially weakens the assumptions that formal analyses can (soundly) make. Moreover, the core functionality of smart contracts is to manipulate and transfer resources; describing this functionality concisely requires dedicated specification support. Current reasoning techniques do not fully address these challenges, being restricted in their scope or expressiveness (in particular, in the presence of re-entrant calls), and offering limited means of expressing the resource transfers a contract performs. In this paper, we present a novel specification methodology tailored to the domain of smart contracts. Our specification constructs and associated reasoning technique are the first to enable: (1) sound and precise reasoning in the presence of unverified code and arbitrary re-entrancy, (2) modular reasoning about collaborating smart contracts, and (3) domain-specific specifications based on resources and resource transfers, which allow expressing a contract's behavior in intuitive and concise ways and exclude typical errors by default. We have implemented our approach in 2vyper, an SMT-based automated verification tool for Ethereum smart contracts written in the Vyper language, and demonstrated its effectiveness in succinctly capturing and verifying strong correctness guarantees for real-world contracts.
This paper presents SAILFISH, a scalable system for automatically finding state-inconsistency bugs in smart contracts. To make the analysis tractable, we introduce a hybrid approach that includes (i) a light-weight exploration phase that dramatically reduces the number of instructions to analyze, and (ii) a precise refinement phase based on symbolic evaluation guided by our novel value-summary analysis, which generates extra constraints to over-approximate the side effects of whole-program execution, thereby ensuring the precision of the symbolic evaluation. We developed a prototype of SAILFISH and evaluated its ability to detect two state-inconsistency flaws, viz., reentrancy and transaction order dependence (TOD) in Ethereum smart contracts. Further, we present detection rules for other kinds of smart contract flaws that SAILFISH can be extended to detect. Our experiments demonstrate the efficiency of our hybrid approach as well as the benefit of the value summary analysis. In particular, we show that S SAILFISH outperforms five state-of-the-art smart contract analyzers (SECURITY, MYTHRIL, OYENTE, SEREUM and VANDAL ) in terms of performance, and precision. In total, SAILFISH discovered 47 previously unknown vulnerable smart contracts out of 89,853 smart contracts from ETHERSCAN .
Ethan Cecchetti, Siqiu Yao, Haobin Ni, Andrew C. Myers
The disastrous vulnerabilities in smart contracts sharply remind us of our ignorance: we do not know how to write code that is secure in composition with malicious code. Information flow control has long been proposed as a way to achieve compositional security, offering strong guarantees even when combining software from different trust domains. Unfortunately, this appealing story breaks down in the presence of reentrancy attacks. We formalize a general definition of reentrancy and introduce a security condition that allows software modules like smart contracts to protect their key invariants while retaining the expressive power of safe forms of reentrancy. We present a security type system that provably enforces secure information flow; in conjunction with run-time mechanisms, it enforces secure reentrancy even in the presence of unknown code; and it helps locate and correct recent high-profile vulnerabilities.
The growing adoption of smart contracts on blockchains poses new security risks that can lead to significant monetary loss, while existing approaches either provide no (or partial) security guarantees for smart contracts or require huge proof effort. To address this challenge, we present SciviK, a versatile framework for specifying and verifying industrial-grade smart contracts. SciviK's versatile approach extends previous efforts with three key contributions: (i) an expressive annotation system enabling built-in directives for vulnerability pattern checking, neural-based loop invariant inference, and the verification of rich properties of real-world smart contracts (ii) a fine-grained model for the Ethereum Virtual Machine (EVM) that provides low-level execution semantics, (iii) an IR-level verification framework integrating both SMT solvers and the Coq proof assistant. We use SciviK to specify and verify security properties for 12 benchmark contracts and a real-world Decentralized Finance (DeFi) smart contract. Among all 158 specified security properties (in six types), 151 properties can be automatically verified within 2 seconds, five properties can be automatically verified after moderate modifications, and two properties are manually proved with around 200 lines of Coq code.
Zihan Zhao, Sidi Mohamed Beillahi, Ryan Song, Yuxi Cai · 6 authors
This paper presents SigVM, a novel blockchain virtual machine that supports an event-driven execution model, enabling developers to build autonomous smart contracts. Contracts in SigVM can emit signal events, on which other contracts can listen. Once an event is triggered, corresponding handler functions are automatically executed as signal transactions. We build an end-to-end blockchain platform SigChain and a contract language compiler SigSolid to realize the potential of SigVM. Experimental results show that our benchmark applications can be reimplemented with SigVM in an autonomous way, eliminating the dependency on unreliable mechanisms like off-chain relay servers. The development effort of reimplementing these contracts with SigVM is small, i.e., we modified on average 2.6% of the contract code.
Abstract A smart contract is a program executed on a blockchain, based on which many cryptocurrencies are implemented, and is being used for automating transactions. Due to the large amount of money that smart contracts deal with, there is a surging demand for a method that can statically and formally verify them. This tool paper describes our type-based static verification tool Helmholtz for Michelson, which is a statically typed stack-based language for writing smart contracts that are executed on the blockchain platform Tezos. Helmholtz is designed on top of our extension of Michelson’s type system with refinement types. Helmholtz takes a Michelson program annotated with a user-defined specification written in the form of a refinement type as input; it then typechecks the program against the specification based on the refinement type system, discharging the generated verification conditions with the SMT solver Z3. We briefly introduce our refinement type system for the core calculus Mini-Michelson of Michelson, which incorporates the characteristic features such as compound datatypes (e.g., lists and pairs), higher-order functions, and invocation of another contract. Helmholtz successfully verifies several practical Michelson programs, including one that transfers money to an account and that checks a digital signature.
Smart contract vulnerability detection draws extensive attention in recent years due to the substantial losses caused by hacker attacks. Existing efforts for contract security analysis heavily rely on rigid rules defined by experts, which are labor-intensive and non-scalable. More importantly, expert-defined rules tend to be error-prone and suffer the inherent risk of being cheated by crafty attackers. Recent researches focus on the symbolic execution and formal analysis of smart contracts for vulnerability detection, yet to achieve a precise and scalable solution. Although several methods have been proposed to detect vulnerabilities in smart contracts, there is still a lack of effort that considers combining expert-defined security patterns with deep neural networks. In this paper, we explore using graph neural networks and expert knowledge for smart contract vulnerability detection. Specifically, we cast the rich control- and data- flow semantics of the source code into a contract graph. To highlight the critical nodes in the graph, we further design a node elimination phase to normalize the graph. Then, we propose a novel temporal message propagation network to extract the graph feature from the normalized graph, and combine the graph feature with designed expert patterns to yield a final detection system. Extensive experiments are conducted on all the smart contracts that have source code in Ethereum and VNT Chain platforms. Empirical results show significant accuracy improvements over the state-of-the-art methods on three types of vulnerabilities, where the detection accuracy of our method reaches 89.15%, 89.02%, and 83.21% for reentrancy, timestamp dependence, and infinite loop vulnerabilities, respectively.
Dec 16, 2020·CPP'2021: Proceedings of the 10th ACM SIGPLAN International Conference on Certified Programs and Proofs, January 18--19, 2021, Virtual, Denmark
Danil Annenkov, Mikkel Milo, Jakob Botsch Nielsen, Bas Spitters
We implement extraction of Coq programs to functional languages based on MetaCoq's certified erasure. As part of this, we implement an optimisation pass removing unused arguments. We prove the pass correct wrt. a conventional call-by-value operational semantics of functional languages. We apply this to two functional smart contract languages, Liquidity and Midlang, and to the functional language Elm. Our development is done in the context of the ConCert framework that enables smart contract verification. We contribute a verified boardroom voting smart contract featuring maximum voter privacy such that each vote is kept private except under collusion of all other parties. We also integrate property-based testing into ConCert using QuickChick and our development is the first to support testing properties of interacting smart contracts. We test several complex contracts such as a DAO-like contract, an escrow contract, an implementation of a Decentralized Finance (DeFi) contract which includes a custom token standard (Tezos FA2), and more. In total, this gives us a way to write dependent programs in Coq, test them semi-automatically, verify, and then extract to functional smart contract languages, while retaining a small trusted computing base of only MetaCoq and the pretty-printers into these languages.
Blockchains host smart contracts for crowdfunding, tokens, and many other purposes. Vulnerabilities in contracts are often discovered, leading to the loss of large quantities of money. Psamathe is a new language we are designing around a new flow abstraction, reducing asset bugs and making contracts more concise than in existing languages. We present an overview of Psamathe, including a partial formalization. We also discuss several example contracts in Psamathe, and compare the Psamathe examples to the same contracts written in Solidity.
Nick Baumann, Samuel Steffen, Benjamin Bichsel, Petar Tsankov · 5 authors
Recent work introduces zkay, a system for specifying and enforcing data privacy in smart contracts. While the original prototype implementation of zkay (v0.1) demonstrates the feasibility of the approach, its proof-of-concept implementation suffers from severe limitations such as insecure encryption and lack of important language features. In this report, we present zkay v0.2, which addresses its predecessor's limitations. The new implementation significantly improves security, usability, modularity, and performance of the system. In particular, zkay v0.2 supports state-of-the-art asymmetric and hybrid encryption, introduces many new language features (such as function calls, private control flow, and extended type support), allows for different zk-SNARKs backends, and reduces both compilation time and on-chain costs.
Vaivaswatha Nagaraj, Jacob Johannsen, Anton Trunov, George Pîrlea · 6 authors
Scilla is a higher-order polymorphic typed intermediate level language for implementing smart contracts. In this talk, we describe a Scilla compiler targeting LLVM, with a focus on mapping Scilla types, values, and its functional language constructs to LLVM-IR. The compiled LLVM-IR, when executed with LLVM's JIT framework, achieves a speedup of about 10x over the reference interpreter on a typical Scilla contract. This reduced latency is crucial in the setting of blockchains, where smart contracts are executed as parts of transactions, to achieve peak transactions processed per second. Experiments on the Ackermann function achieved a speedup of more than 45x. This talk abstract is aimed at both programming language researchers looking to implement an LLVM based compiler for their functional language, as well as at LLVM practitioners.
Ashish Rajendra Sai, Conor Holmes, Jim Buckley, Andrew Le Gear
Blockchain systems have gained substantial traction recently, partly due to the potential of decentralized immutable mediation of economic activities. Ethereum is a prominent example that has the provision for executing stateful computing scripts known as Smart Contracts. These smart contracts resemble traditional programs, but with immutability being the core differentiating factor. Given their immutability and potential high monetary value, it becomes imperative to develop high-quality smart contracts. Software metrics have traditionally been an essential tool in determining programming quality. Given the similarity between smart contracts (written in Solidity for Ethereum) and object-oriented (OO) programming, OO metrics would appear applicable. In this paper, we empirically evaluate inheritance-based metrics as applied to smart contracts. We adopt this focus because, traditionally, inheritance has been linked to a more complex codebase which we posit is not the case with Solidity based smart contracts. In this work, we evaluate the hypothesis that, due to the differences in the context of smart contracts and OO programs, it may not be appropriate to use the same interpretation of inheritance based metrics for assessment.
Luís Pedro Arrojado da Horta, João Santos Reis, Mário Pereira, Simão Melo de Sousa
This paper introduces WhylSon, a deductive verification tool for smart contracts written in Michelson, which is the low-level language of the Tezos blockchain. WhylSon accepts a formally specified Michelson contract and automatically translates it to an equivalent program written in WhyML, the programming and specification language of the Why3 framework. Smart contract instructions are mapped into a corresponding WhyML shallow-embedding of the their axiomatic semantics, which we also developed in the context of this work. One major advantage of this approach is that it allows an out-of-the-box integration with the Why3 framework, namely its VCGen and the backend support for several automated theorem provers. We also discuss the use of WhylSon to automatically prove the correctness of diverse annotated smart contracts.
Events in the Solidity language provide a means of communication between the on-chain services of decentralized applications and the users of those services. Events are commonly used as an abstraction of contract execution that is relevant from the users' perspective. Users must, therefore, be able to understand the meaning and trust the validity of the emitted events. This paper presents a source-level approach for the formal specification and verification of Solidity contracts with the primary focus on events. Our approach allows specification of events in terms of the on-chain data that they track, and predicates that define the correspondence between the blockchain state and the abstract view provided by the events. The approach is implemented in solc-verify, a modular verifier for Solidity, and we demonstrate its applicability with various examples.
Clara Schneidewind, Ilya Grishchenko, Markus Scherer, Matteo Maffei
Ethereum has emerged as the most popular smart contract development platform, with hundreds of thousands of contracts stored on the blockchain and covering a variety of application scenarios, such as auctions, trading platforms, and so on. Given their financial nature, security vulnerabilities may lead to catastrophic consequences and, even worse, they can be hardly fixed as data stored on the blockchain, including the smart contract code itself, are immutable. An automated security analysis of these contracts is thus of utmost interest, but at the same time technically challenging for a variety of reasons, such as the specific transaction-oriented programming mechanisms, which feature a subtle semantics, and the fact that the blockchain data which the contract under analysis interacts with, including the code of callers and callees, are not statically known. In this work, we present eThor, the first sound and automated static analyzer for EVM bytecode, which is based on an abstraction of the EVM bytecode semantics based on Horn clauses. In particular, our static analysis supports reachability properties, which we show to be sufficient for capturing interesting security properties for smart contracts (e.g., single-entrancy) as well as contract-specific functional properties. Our analysis is proven sound against a complete semantics of EVM bytecode and an experimental large-scale evaluation on real-world contracts demonstrates that eThor is practical and outperforms the state-of-the-art static analyzers: specifically, eThor is the only one to provide soundness guarantees, terminates on 95% of a representative set of real-world contracts, and achieves an F-measure (which combines sensitivity and specificity) of 89%.
The EVM language is a simple stack-based language with words of 256 bits, with one significant difference between the EVM and other virtual machine languages (like Java Bytecode or CLI for .Net programs): the use of the stack for saving the jump addresses instead of having it explicit in the code of the jumping instructions. Static analyzers need the complete control flow graph (CFG) of the EVM program in order to be able to represent all its execution paths. This report addresses the problem of obtaining a precise and complete stack-sensitive CFG by means of a static analysis, cloning the blocks that might be executed using different states of the execution stack. The soundness of the analysis presented is proved.
Sam Blackshear, David L. Dill, Shaz Qadeer, Clark W. Barrett · 7 authors
Smart contracts are programs that implement potentially sophisticated transactions on modern blockchain platforms. In the rapidly evolving blockchain environment, smart contract programming languages must allow users to write expressive programs that manage and transfer assets, yet provide strong protection against sophisticated attacks. Addressing this need, we present flexible and reliable abstractions for programming with digital currency in the Move language [Blackshear et al. 2019]. Move uses novel linear [Girard 1987] resource types with semantics drawing on C++11 [Stroustrup 2013] and Rust [Matsakis and Klock 2014]: when a resource value is assigned to a new memory location, the location previously holding it must be invalidated. In addition, a resource type can only be created or destroyed by procedures inside its declaring module. We present an executable bytecode language with resources and prove that it enjoys resource safety, a conservation property for program values that is analogous to conservation of mass in the physical world.
Smart contract (SC) platforms form blocks of transactions into a chain and execute them via user-defined smart contracts. In conventional platforms like Bitcoin and Ethereum, the transactions within a block are executed \emph{sequentially} by the miner and are then validated \emph{sequentially} by the validators to reach consensus about the final state of the block. In order to leverage the advances of multicores, this paper explores the next generation of smart contract platforms that enables concurrent execution of such contracts. Reasoning about the validity of the object states is challenging in concurrent smart contracts. We examine a programming model to support \emph{optimistic} execution of SCTs. We introduce a novel programming language, so-called OV, and a Solidity API to ease programing of optimistic smart contracts. OV language together with static checking will help reasoning about a crucial property of optimistically executed smart contracts -- the validity of object states in trustless systems.
We propose SessionC#, a lightweight session typed library for safe concurrent/distributed programming. The key features are (1) the improved fluent interface which enables writing communication in chained method calls, by exploiting C#'s out variables, and (2) amalgamation of session delegation with async/await, which materialises session cancellation in a limited form, which we call session intervention. We show the effectiveness of our proposal via a Bitcoin miner application.
Michael Coblenz, Jonathan Aldrich, Brad A. Myers, Joshua Sunshine
Some blockchain programs (smart contracts) have included serious security vulnerabilities. Obsidian is a new typestate-oriented programming language that uses a strong type system to rule out some of these vulnerabilities. Although Obsidian was designed to promote usability to make it as easy as possible to write programs, strong type systems can cause a language to be difficult to use. In particular, ownership, typestate, and assets, which Obsidian uses to provide safety guarantees, have not seen broad adoption together in popular languages and result in significant usability challenges. We performed an empirical study with 20 participants comparing Obsidian to Solidity, which is the language most commonly used for writing smart contracts today. We observed that Obsidian participants were able to successfully complete more of the programming tasks than the Solidity participants. We also found that the Solidity participants commonly inserted asset-related bugs, which Obsidian detects at compile time.