We present Harvey, an industrial greybox fuzzer for smart contracts,
which are programs managing accounts on a blockchain.
Greybox fuzzing is a lightweight test-generation approach that
effectively detects bugs and security vulnerabilities. However,
greybox fuzzers randomly mutate program inputs to exercise new paths;
this makes it challenging to cover code that is guarded by narrow
checks. Moreover, most real-world smart contracts transition through
many different states during their lifetime, e.g., for every bid in an
auction. To explore these states and thereby detect deep
vulnerabilities, a greybox fuzzer would need to generate sequences of
contract transactions, e.g., by creating bids from multiple users,
while keeping the search space and test suite tractable.
In this paper, we explain how Harvey alleviates both
challenges with two key techniques. First, Harvey extends standard greybox fuzzing with
a method for predicting new inputs that are more likely to cover new
paths or reveal vulnerabilities in smart contracts. Second, it fuzzes
transaction sequences in a targeted and demand-driven way. We have
evaluated our approach on 27 real-world contracts. Our experiments
show that our techniques significantly increase Harvey's
effectiveness in achieving high coverage and detecting
vulnerabilities, in most cases orders-of-magnitude faster.