Cryptology ePrint Archive: Report 2017/1090

Enter the Hydra: Towards Principled Bug Bounties and Exploit-Resistant Smart Contracts

Lorenz Breidenbach and Philip Daian and Florian Tramèr and Ari Juels

Abstract: Bug bounties are a popular tool to help prevent software exploits. Yet, they lack rigorous principles for setting bounty amounts and require high payments to attract economically rational hackers. Rather than claim bounties for serious bugs, hackers often sell or exploit them.

We present the *Hydra Framework*, the first general, principled approach to modeling and administering bug bounties that incentivize bug disclosure. Our key idea is an *exploit gap*, a program transformation that enables runtime detection, and rewarding, of critical bugs. Our framework transforms programs via *N-of-N-version programming*, a variant of classical N-version programming that runs multiple independent program instances.

We apply the Hydra Framework to *smart contracts*, small programs that execute on blockchains. We show how Hydra contracts greatly amplify the power of bounties to incentivize bug disclosure by economically rational adversaries, establishing the first framework for rigorous economic evaluation of smart contract security. We also model powerful adversaries capable of *bug withholding*, exploiting race conditions in blockchains to claim bounties before honest users can. We present *Submarine Commitments*, a countermeasure of independent interest that conceals transactions on blockchains.

We design a simple, automated version of the Hydra Framework for Ethereum (ethereum.org) and implement two Hydra contracts, an ERC20 standard token and a Monty-Hall game. We evaluate our implementation for completeness and soundness with the official Ethereum virtual machine test suite and live blockchain data.

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Date: received 9 Nov 2017, last revised 12 Feb 2018

Contact author: tramer at cs stanford edu

Available format(s): PDF | BibTeX Citation

Note: Added experimental / implementation results and testing methodology and removed some less relevant information about front-running.

Version: 20180212:211455 (All versions of this report)

Short URL: ia.cr/2017/1090

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