OpenAI's Latest Experiment: Can AI Agents Read Smart Contracts?

OpenAI has launched a new study to measure whether autonomous systems can understand and secure blockchain code. The project explores a critical question for the future of digital finance, can machines reliably detect weaknesses in smart contracts before attackers do?

The initiative reflects growing concern across the industry. With billions of dollars locked in decentralized applications and cyber theft continuing to rise, the need for faster and more scalable security tools has become urgent. 

The OpenAI smart contract experiment aims to evaluate how well advanced models perform when faced with real economic consequences, offering new insight into the future of AI agents crypto security.

Key Takeaways

• OpenAI introduced EVMbench to test how effectively OpenAI AI agents can detect and exploit smart contract vulnerabilities.

• Early results show leading models can identify flaws worth tens of thousands of dollars in simulated rewards.

• The research highlights the growing role of AI blockchain security research as both a defensive and potential offensive tool.

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Testing AI in Real Financial Conditions

OpenAI recently published a research paper titled EVMbench: Evaluating AI Agents on Smart Contract Security. The study was conducted with crypto investment firm Paradigm and security auditor OtterSec.

The benchmark evaluates how well different models perform when asked to identify, patch, and sometimes exploit vulnerabilities in Ethereum based code. 

Instead of measuring accuracy alone, the test assigns a monetary value to each discovered flaw. This approach creates what researchers call an economically meaningful environment.

Smart contracts currently secure assets worth billions. Testing AI reading smart contracts in purely academic conditions would not reflect real world risk. By linking performance to financial impact, EVMbench attempts to simulate the incentives that drive both security researchers and attackers.

The benchmark includes 120 vulnerabilities drawn from 40 real audits, many sourced from open audit competitions. OpenAI hopes that EVMbench OpenAI will become a long term AI smart contract security benchmark to track progress over time.

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Which AI Models Performed Best?

The early results show that advanced models are already capable of meaningful security analysis.

Anthropic’s Claude Opus 4.6 achieved the highest average detection value at $37,824. OpenAI’s OC GPT 5.2 followed with $31,623, while Google’s Gemini 3 Pro recorded $25,112.

These figures represent the simulated financial value of vulnerabilities identified during testing. While the numbers do not reflect actual payouts, they suggest that modern AI systems are approaching the level of skilled human auditors in certain tasks.

At the same time, OpenAI emphasized that the technology is still developing. Complex logic errors and novel attack patterns remain difficult for automated systems to identify reliably.

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Why Smart Contract Security Needs AI

The timing of the experiment reflects growing concern across the crypto industry. In 2025 alone, attackers stole $3.4 billion in digital assets, slightly higher than the previous year.

Manual audits remain essential, but they are time consuming and expensive. As decentralized finance expands, human teams alone may struggle to keep up. 

This is where AI auditing Ethereum contracts could play a critical role by scanning large volumes of code quickly and continuously.

Researchers also warn that the technology has a dual nature. The same tools that help defenders find weaknesses could also be used by attackers to discover exploits faster. Understanding AI performance early is therefore a key step in managing future risk.

The Bigger Picture: AI Agents and Autonomous Finance

The OpenAI study also reflects a broader shift toward autonomous financial systems. Industry leaders increasingly expect software agents to manage transactions on behalf of users.

Circle CEO Jeremy Allaire has predicted that billions of AI agents could use stablecoins for everyday payments within five years. Former Binance chief Changpeng Zhao has also suggested that cryptocurrency may become the native payment system for machine driven economies.

Some analysts believe AI may even solve one of crypto’s long standing usability challenges. Dragonfly managing partner Haseeb Qureshi recently argued that blockchain systems feel intimidating because they were not designed for human intuition. 

He suggested that self driving wallets powered by AI could handle complex operations and reduce the risk of user error.

If that vision becomes reality, strong AI blockchain security research will be essential to ensure those agents act safely and reliably.

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Conclusion

The OpenAI smart contract experiment marks an important step toward understanding how artificial intelligence may reshape blockchain security. 

Early results show that advanced models can already detect vulnerabilities with meaningful financial impact, suggesting a future where automated tools support or even augment human auditors.

At the same time, the research highlights a growing challenge. As AI capabilities improve, the same technology could strengthen both defenders and attackers. Establishing benchmarks like EVMbench will be critical for tracking progress and managing risk.

For an industry built on code and automation, the ability of machines to read and secure smart contracts may soon become a defining factor in the safety of digital finance.

FAQ

What is the OpenAI smart contract experiment?

It is a research initiative that tests how well AI agents can detect, fix, and exploit vulnerabilities in Ethereum smart contracts using the EVMbench framework.

What is EVMbench OpenAI?

EVMbench is a benchmark that evaluates AI performance on 120 real world smart contract vulnerabilities based on their financial impact.

Can AI fully replace human smart contract auditors?

Not yet. AI can assist with large scale analysis, but human expertise is still needed for complex logic review and final validation.

Why is AI reading smart contracts important?

Smart contracts manage billions of dollars. Automated analysis can improve speed, reduce costs, and help identify risks before attackers exploit them.

How does this relate to crypto security?

The study contributes to AI agents crypto security by helping researchers understand how autonomous systems may protect or threaten blockchain applications in the future.

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