  In this work we propose Dynamit, a monitoring framework to detect reentrancy
vulnerabilities in Ethereum smart contracts. The novelty of our framework is
that it relies only on transaction metadata and balance data from the
blockchain system; our approach requires no domain knowledge, code
instrumentation, or special execution environment. Dynamit extracts features
from transaction data and uses a machine learning model to classify
transactions as benign or harmful. Therefore, not only can we find the
contracts that are vulnerable to reentrancy attacks, but we also get an
execution trace that reproduces the attack.
