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Annotary: A Concolic Execution System for Developing Secure Smart Contracts

: Weiss, K.; Schütte, J.


Sako, Kazue:
Computer Security - ESORICS 2019 : 24th European Symposium on Research in Computer Security, Luxembourg, September 23-27, 2019, Proceedings, Part I
Cham: Springer Nature, 2019 (Lecture Notes in Computer Science 11735)
ISBN: 978-3-030-29958-3 (Print)
ISBN: 978-3-030-29959-0
European Symposium on Research in Computer Security (ESORICS) <24, 2019, Luxembourg>
Fraunhofer AISEC ()

Ethereum smart contracts are executable programs, deployed on a peer-to-peer network and executed in a consensus-based fashion. Their bytecode is public, immutable and once deployed to the blockchain, cannot be patched anymore. As smart contracts may hold Ether worth of several million dollars, they are attractive targets for attackers and indeed some contracts have successfully been exploited in the recent past, resulting in tremendous financial losses. The correctness of smart contracts is thus of utmost importance. While first approaches on formal verification exist, they demand users to be well-versed in formal methods which are alien to many developers and are only able to analyze individual contracts, without considering their execution environment, i.e., calls to external contracts, sequences of transaction, and values from the actual blockchain storage. In this paper, we present Annotary, a concolic execution framework to analyze smart contracts for vulnerabilities, supported by annotations which developers write directly in the Solidity source code. In contrast to existing work, Annotary supports analysis of inter-transactional, inter-contract control flows and combines symbolic execution of EVM bytecode with a resolution of concrete values from the public Ethereum blockchain. While the analysis of Annotary tends to weight precision higher than soundness, we analyze inter-transactional call chains to eliminate false positives from unreachable states that traditional symbolic execution would not be able to handle. We present the annotation and analysis concepts of Annotary, explain its implementation on top of the Laser symbolic virtual machine, and demonstrate its usage as a plugin for the Sublime Text editor.