Computer Science > Cryptography and Security
[Submitted on 23 Aug 2021 (v1), last revised 4 Jul 2022 (this version, v3)]
Title:Elysium: Context-Aware Bytecode-Level Patching to Automatically Heal Vulnerable Smart Contracts
View PDFAbstract:Fixing bugs is easiest by patching source code. However, source code is not always available: only 0.3% of the ~49M smart contracts that are currently deployed on Ethereum have their source code publicly available. Moreover, since contracts may call functions from other contracts, security flaws in closed-source contracts may affect open-source contracts as well. However, current state-of-the-art approaches that operate on closed-source contracts (i.e., EVM bytecode), such as EVMPatch and SmartShield, make use of purely hard-coded templates that leverage fix patching patterns. As a result, they cannot dynamically adapt to the bytecode that is being patched, which severely limits their flexibility and scalability. For instance, when patching integer overflows using hard-coded templates, a particular patch template needs to be employed as the bounds to be checked are different for each integer size. In this paper, we propose Elysium, a scalable approach towards automatic smart contract repair at the bytecode level. Elysium combines template-based and semantic-based patching by inferring context information from bytecode. Elysium is currently able to patch 7 different types of vulnerabilities in smart contracts automatically and can easily be extended with new templates and new bug-finding tools. We evaluate its effectiveness and correctness using 3 different datasets by replaying more than 500K transactions on patched contracts. We find that Elysium outperforms existing tools by patching at least 30% more contracts correctly. Finally, we also compare the overhead of Elysium in terms of deployment and transaction cost. In comparison to other tools, we find that generally Elysium minimizes the runtime cost (i.e., transaction cost) up to a factor of 1.7, for only a marginally higher deployment cost, where deployment cost is a one-time cost as compared to the runtime cost.
Submission history
From: Christof Ferreira Torres [view email][v1] Mon, 23 Aug 2021 11:10:30 UTC (645 KB)
[v2] Wed, 25 Aug 2021 19:16:09 UTC (644 KB)
[v3] Mon, 4 Jul 2022 20:59:11 UTC (1,035 KB)
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