  The use of blockchains for automated and adversarial trading has become
commonplace. However, due to the transparent nature of blockchains, an
adversary is able to observe any pending, not-yet-mined transactions, along
with their execution logic. This transparency further enables a new type of
adversary, which copies and front-runs profitable pending transactions in
real-time, yielding significant financial gains.
  Shedding light on such "copy-paste" malpractice, this paper introduces the
Blockchain Imitation Game and proposes a generalized imitation attack
methodology called Ape. Leveraging dynamic program analysis techniques, Ape
supports the automatic synthesis of adversarial smart contracts. Over a
timeframe of one year (1st of August, 2021 to 31st of July, 2022), Ape could
have yielded 148.96M USD in profit on Ethereum, and 42.70M USD on BNB Smart
Chain (BSC).
  Not only as a malicious attack, we further show the potential of transaction
and contract imitation as a defensive strategy. Within one year, we find that
Ape could have successfully imitated 13 and 22 known Decentralized Finance
(DeFi) attacks on Ethereum and BSC, respectively. Our findings suggest that
blockchain validators can imitate attacks in real-time to prevent intrusions in
DeFi.
