MadMax: surviving out-of-gas conditions in Ethereum smart contracts

Abstract

Ethereum is a distributed blockchain platform, serving as an ecosystem for smart contracts: full-fledged intercommunicating programs that capture the transaction logic of an account. Unlike programs in mainstream languages, a gas limit restricts the execution of an Ethereum smart contract: execution proceeds as long as gas is available. Thus, gas is a valuable resource that can be manipulated by an attacker to provoke unwanted behavior in a victim's smart contract (e.g., wasting or blocking funds of said victim). Gas-focused vulnerabilities exploit undesired behavior when a contract (directly or through other interacting contracts) runs out of gas. Such vulnerabilities are among the hardest for programmers to protect against, as out-of-gas behavior may be uncommon in non-attack scenarios and reasoning about it is far from trivial. In this paper, we classify and identify gas-focused vulnerabilities, and present MadMax: a static program analysis technique to automatically detect gas-focused vulnerabilities with very high confidence. Our approach combines a control-flow-analysis-based decompiler and declarative program-structure queries. The combined analysis captures high-level domain-specific concepts (such as łdynamic data structure storagež and łsafely resumable loopsž) and achieves high precision and scalability. MadMax analyzes the entirety of smart contracts in the Ethereum blockchain in just 10 hours (with decompilation timeouts in 8% of the cases) and flags contracts with a (highly volatile) monetary value of over $2.8B as vulnerable. Manual inspection of a sample of flagged contracts shows that 81% of the sampled warnings do indeed lead to vulnerabilities, which we report on in our experiment. CCS Concepts: • Software and its engineering → General programming languages;

SAFEVM: a safety verifier for Ethereum smart contracts

“…Verification of Ethereum smart contracts for potential safety and security vulnerabilities is becoming a popular research topic with numerous tools being developed, among them, we have tools based on symbolic execution [18,13,20,17,15,21], tools based on SMT solving [19,16], and other tools based on certified programming [7,12,5]. There are some tools also that aim at detecting, analyzing and verifying non-functional properties of smart contracts, e.g., those focused on reasoning about the gas consumption [4,10,11,19].…”

An overview on smart contracts: Challenges, advances and platforms

“…Liu et al [40] proposed to perform the fuzz testing on smart contracts by iteratively generating random but diverse transactions to detect reentrancy bugs. 1) Readability • Human readable code [34], [35] • Human readable execution [36], [37] • Re-entrancy [38], [39], [40] 2) Functional issues • Block randness [41], [42], [43] • Overcharging [44], [45] Deployment • Bytecode analysis [46], [47], [48], [49], [50], [51], [52], [53] 1) Contract correctness • Source code analysis [54], [55], [56], [57] • Machine learning based analysis [58], [59], [60] • Graph based analysis [61], [62] 2) Dynamic control flow • Path-searching [63] • Execution environment [64] Execution 1) Trustworthy oracle • Third-party involved [65] • Decentralized [66], [67] 2) Transaction-ordering dependence • Sequential execution [68] • Predefining contract [69] 3) Execution efficiency • Execution serialization [70], [71], [72] • Inspection of contract [73] Completion 1) Privacy and Security • Privacy [74],…”

GASOL: Gas Analysis and Optimization for Ethereum Smart Contracts

“…The purpose of the Gasper and MadMax tools is precisely the detection of gas related vulnerabilities. MadMax [13] focuses on identifying control-and data-flow patterns inherent for the gas-related vulnerabilities, thus, it works as a bug-finder, rather than as a gas analyzer like Gasol.…”