Talks and Poster Presentations (with Proceedings-Entry):

C. Schneidewind, I. Grishchenko, M. Scherer, M. Maffei:
"eThor: Practical and Provably Sound Static Analysis of Ethereum Smart Contracts";
Talk: ACM Conference on Computer and Communications Security (CCS), Orlando; 2020-11-09 - 2020-11-13; in: "CCS '20: Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security", Association for Computing Machinery ACM, (2020), ISBN: 978-1-4503-7089-9; 621 - 640.

English abstract:
Ethereum has emerged as the most popular smart contract platform, with hundreds of thousands of contracts stored on the blockchain and covering diverse application scenarios, such as auctions, trading platforms, or elections. Given the financial nature of smart contracts, security vulnerabilities may lead to catastrophic consequences and, even worse, can hardly be 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. This is as e.g., Ethereum's transaction-oriented programming mechanisms feature a subtle semantics, and since the blockchain data at execution time, 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 a large-scale experimental 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 94% of a representative set of real-world contracts, and achieves an F-measure (which combines sensitivity and specificity) of 89%.

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Electronic version of the publication:

Created from the Publication Database of the Vienna University of Technology.