At the rapid intersection of artificial intelligence and blockchain technology, OpenAI led by Sam Altman has partnered with crypto investment giant Paradigm to officially launch EVMbench. This new benchmarking tool aims to rigorously evaluate whether AI agents can effectively detect, patch, and even simulate high-risk vulnerabilities in Ethereum smart contracts, safeguarding digital assets worth hundreds of billions of dollars.
(Background: Are cryptocurrencies never designed for humans? Dragonfly partner: The true users are AI agents.)
(Additional context: Sam Altman personally recruited! OpenClaw founder joins OpenAI, with personal AI agents “soon becoming core products.”)
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As AI technology advances rapidly, OpenAI recently announced a collaboration with crypto investment firm Paradigm to launch the new benchmark tool “EVMbench.” This tool is specifically designed to assess the performance of AI agents in the field of blockchain smart contract security. OpenAI states that this move aims to establish clearer AI evaluation standards for blockchain security while addressing the increasing need to protect assets in the decentralized finance (DeFi) sector.
Smart contracts are self-executing code deployed on Ethereum Virtual Machine (EVM)-compatible blockchains and have become the core infrastructure supporting decentralized exchanges, lending platforms, and stablecoin payments. Currently, the total value of open-source crypto assets protected by these contracts often exceeds $100 billion. Since these contracts are usually immutable once on-chain, any vulnerabilities can lead to massive fund losses. Several high-profile attacks have occurred over the past years. Therefore, effective auditing and strengthening of smart contract security have become one of the most urgent issues in the blockchain industry.
EVMbench is based on real-world cases, collecting 120 severe vulnerabilities from 40 audit projects, most of which come from public code audit competitions like Code4rena, and additionally incorporating Paradigm-supported vulnerabilities related to Tempo blockchain payments. The test covers three core capabilities:
Through these three aspects, EVMbench provides a percentage-based overall performance score, allowing researchers and developers to clearly compare different AI models’ capabilities in smart contract security tasks.
OpenAI emphasizes in its official blog that as AI agents’ abilities to read, write, and execute code continue to improve, their role in highly valuable environments will become increasingly critical for defense. EVMbench is not only a test of AI limits but also aims to encourage the industry to apply AI to proactive auditing and reinforcement of deployed contracts, thereby reducing overall risk.
OpenAI also notes that this benchmark aligns closely with the “Preparedness Framework” describing high-risk network scenarios, demonstrating its comprehensive approach to AI security governance.
The launch of EVMbench marks AI technology’s transition from general applications to highly specialized blockchain security. As DeFi and stablecoin payments continue to grow, reliable AI performance in detecting and patching vulnerabilities could significantly enhance the entire ecosystem’s security. However, the benchmark also reminds us that AI’s ability to exploit vulnerabilities must be strictly regulated to prevent malicious use. As AI models advance, EVMbench may become an important indicator of whether AI is capable of safeguarding digital assets.
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