teEther: Gnawing at Ethereum to Automatically Exploit Smart Contracts

By Johannes Krupp, Christian Rossow. USENIX Security Symposium, 2018

355 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/6e463cb9776b6864570005b742bc963519b7ff6d

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Citations in the corpus

Slither: A Static Analysis Framework for Smart Contracts (2019, methodology): “Finally, TeEther is an automatic exploit generation tool for certain types of vulnerabilities in Ethereum smart contracts created by Krupp and Rossow [13].”
sFuzz: An Efficient Adaptive Fuzzer for Solidity Smart Contracts (2020, methodology): “based on symbolic execution like Oyente [22] and teEther [21] are”
Sereum: Protecting Existing Smart Contracts Against Re-Entrancy Attacks (2018, background): “For instance, Oyente [29], Mythril [31] and Manticore [30] leverage symbolic execution [26] to detect various types of bugs (including re-entrancy) in Ethereum smart contracts. teEther [27] is a tool that automatically generates exploits for smart contracts.”
Erays: Reverse Engineering Ethereum's Opaque Smart Contracts (2018, methodology): “TEETHER [29] is a tool that automatically creates exploits on smart contracts.”
A Survey on Ethereum Systems Security (2019, methodology): “In order to facilitate code-reuse, EVM provides an opcode, DELEGATECALL, for embedding a callee contract’s bytecode into the bytecode of the caller contract as if it’s a piece of the latter’s bytecode [43].”
Manticore: A User-Friendly Symbolic Execution Framework for Binaries and Smart Contracts (2019, methodology): “Symbolic execution in the Ethereum space is much less widely explored, but a few other tools do exist, such as Mythril Classic [2], teEther [10], Oyente [11] and Maian [12].”
Empirical Review of Automated Analysis Tools on 47,587 Ethereum Smart Contracts (2019, unknown): “m/smartdec/smartcheck 29 Solgraph https://github.com/raineorshine/solgraph 30 Solhint https://github.com/protofire/solhint 31 SolMet [20] https://github.com/chicxurug/SolMetSolidity-parser 32 teEther [23] https://github.com/nescio007/teether 33 Vandal [4] https://github.com/usyd-blockchain/vandal 34”
An Overview on Smart Contracts: Challenges, Advances and Platforms (2019, unknown): “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 learni”
Vandal: A Scalable Security Analysis Framework for Smart Contracts (2018, methodology): “The teEther [39] exploit generation tool, although not a decompiler, operates on EVM bytecode and uses a form of iterative data-ﬂow analysis to reconstruct contract control ﬂow graphs. teEther automatically generates exploits for vulnerable contracts us-ing symbolic execution with the Z3 constraint…”
Finding The Greedy, Prodigal, and Suicidal Contracts at Scale (2018, methodology): “Other tools for symbolic analysis of EVM and/or Solidity have been developed more recently:Manticore [27],Mythrill [30, 31], Securify [39], teEther [25], and KEVM [21, 38], all focusing on detecting low-level safety violations and vulnerabilities, such as integer overflows, reentrancy, and unhandled”
Smart Contract Development: Challenges and Opportunities (2021, unknown): “smart contract given its binary code [81].”
Learning to Fuzz from Symbolic Execution with Application to Smart Contracts (2019, background): “Further, existing symbolic execution engines [37, 42] can only symbolically reason limited number of transactions ( e.g. , 3), failing to reach deeper states.”