nevillegrech / MadMax

Ethereum Static Vulnerability Detector for Gas-Focussed Vulnerabilities
BSD 3-Clause "New" or "Revised" License
131 stars 16 forks source link
blockchain-technology decompiler ethereum security-tools

Note: you need to clone this repo using the --recursive flag since this repo has submodules, e.g.,

git clone git@github.com:nevillegrech/MadMax.git --recursive

MadMax

License GitHub Repo stars Twitter Follow

Madmax consists of a series of analyses and queries that find gas-focussed vulnerabilities in Ethereum smart contracts. The analyses are performed on the Gigahose IR, which is lifted from Ethereum bytecode. The first version of MadMax used Vandal.

How to use

First follow the instructions in gigahorse-toolchain for instructions on installation of Gigahorse. In a nutshell, this requires the installation of the Souffle Datalog engine, custom functors and Boost.

In order to run MadMax using Gigahorse, you can use the following incantation:

gigahorse-toolchain/gigahorse.py -C madmax.dl <contract.hex>

Where <contract.hex> is a compiled Ethereum contract, or a directory of contracts. If you're running this for the first time it will take longer due to compilation of Datalog files. The output of the analysis results can be found under .temp/**/out/*.csv and results.json. A summary is also printed to the screen.

To see whether an individual contract is flagged or not if, check whether there are any entries inside the WalletGriefing, UnboundedMassOp and OverflowLoopIterator relations.

Live Deployment

Some of the techniques developed in the MadMax project are now used in Dedaub Watchdog.

Publications

MadMax: surviving out-of-gas conditions in Ethereum smart contracts Neville Grech, Michael Kong, Anton Jurisevic, Lexi Brent, Bernhard Scholz, and Yannis Smaragdakis Proceedings of the ACM in Programming Languages (OOPSLA) 2018 PDF

πŸ† Distinguished Paper πŸ†

MadMax: Analyzing the Out-of-Gas World of Smart Contracts Neville Grech, Michael Kong, Anton Jurisevic, Lexi Brent, Bernhard Scholz, and Yannis Smaragdakis Communications of the ACM 2020 PDF

πŸ† CACM research highlight πŸ†

IMAGE ALT TEXT HERE