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This position paper identifies novel security risks emerging from the intersection of autonomous AI agents and decentralized finance, specifically highlighting how smart contract properties can amplify AI-driven harm. By cataloging three distinct vectors of risk, the authors argue that integrating financial tools into AI workflows requires immediate research into mitigation strategies before widespread adoption occurs. The study underscores a critical safety challenge where standard AI alignment may be insufficient when applied to irreversible blockchain transactions.
Giving AI Agents Access to Cryptocurrency and Smart Contracts Creates New Vectors of AI Harm
arXiv:2507.08249v3 Announce Type: replace Abstract: There is growing interest in giving AI agents access to cryptocurrencies and smart contracts. But doing so, this position paper argues, could spawn categorically new vectors of AI harm. To support this notion, we first examine the unique technical properties of cryptocurrencies and smart contracts that, when paired with AI agents, make this so. Next, we describe three of these new vectors of AI harm in detail, providing a first-of-its-kind taxonomy. Finally, we call for more research into ways to prevent or mitigate these risks, proposing several as a starting point.
Abstract:There is growing interest in giving AI agents access to cryptocurrencies and smart contracts. But doing so, this position paper argues, could spawn categorically new vectors of AI harm. To support this notion, we first examine the unique technical properties of cryptocurrencies and smart contracts that, when paired with AI agents, make this so. Next, we describe three of these new vectors of AI harm in detail, providing a first-of-its-kind taxonomy. Finally, we call for more research into ways to prevent or mitigate these risks, proposing several as a starting point.
Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR)
arXiv:2507.08249 [cs.AI]
(or arXiv:2507.08249v3 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2507.08249 Focus to learn more arXiv-issued DOI via DataCite
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