EVMbench: OpenAI and Paradigm Launch Open-Source Benchmark to Test AI Agents on Smart Contract Security

EVMbench: OpenAI and Paradigm Launch Open-Source Benchmark to Test AI Agents on Smart Contract Security

OpenAI and Paradigm have jointly released EVMbench, an open-source benchmark designed to rigorously evaluate the ability of artificial intelligence agents to identify, analyze, and remediate vulnerabilities in Ethereum Virtual Machine (EVM)-based smart contracts. The initiative, unveiled on February 18, 2026, represents a significant step toward integrating AI into the core of blockchain security infrastructure, addressing the growing threat landscape in decentralized finance (DeFi).

According to Decrypt, EVMbench draws from real-world exploit patterns documented in audited codebases and high-stakes hackathon reports from platforms like Immunefi and HackerOne. The benchmark comprises over 200 synthetic yet realistic smart contract scenarios, each containing known vulnerabilities such as reentrancy attacks, integer overflows, unchecked external calls, and logic flaws in access control. These scenarios are designed to mirror the types of exploits that have led to over $3 billion in losses since 2016, according to blockchain security firm CertiK.

Blockonomi reports that initial benchmarking results compared three leading AI models: OpenAI’s GPT-5, Anthropic’s Claude 3.5, and Google’s Gemini 1.5 Pro. GPT-5 achieved the highest overall accuracy at 87.3%, correctly identifying 174 out of 200 vulnerabilities and proposing accurate fixes in 78% of cases. Claude 3.5 followed closely with 84.1% accuracy, demonstrating superior reasoning in complex state-machine exploits. Gemini 1.5 Pro trailed at 76.8%, struggling particularly with context-dependent vulnerabilities that required understanding of contract inheritance and gas optimization trade-offs.

The benchmark also introduced a novel evaluation metric: “Fix Validity Score,” which measures not just detection accuracy but also the practicality and gas efficiency of proposed patches. This innovation is critical, as many AI-generated fixes, while logically sound, introduce new attack surfaces or increase transaction costs—rendering them unusable in production. EVMbench’s scoring system penalizes such solutions, forcing models to balance security with economic feasibility.

Notably, EVMbench is fully open-source, with all test cases, evaluation scripts, and reference solutions published on GitHub. This transparency enables academic researchers, security auditors, and open-source developers to reproduce results, contribute new test cases, and train their own models. The collaboration between OpenAI, a leader in AI research, and Paradigm, a top-tier crypto investment and infrastructure firm, signals a strategic alignment between AI development and blockchain security needs.

Industry experts have welcomed the initiative. “EVMbench moves us beyond theoretical AI evaluations into practical, domain-specific security testing,” said Dr. Lena Torres, a blockchain security professor at ETH Zurich. “For the first time, we have a standardized way to measure whether AI can truly act as a co-auditor—something that’s urgently needed as DeFi protocols scale.”

However, challenges remain. While AI models excel at pattern recognition, they still struggle with novel attack vectors not present in training data. Additionally, the risk of adversarial manipulation—where malicious actors craft inputs to deceive AI detectors—has not yet been fully tested within the benchmark. OpenAI and Paradigm have pledged to release quarterly updates to EVMbench, incorporating newly discovered exploits and refining evaluation criteria.

The release of EVMbench may catalyze a new wave of AI-augmented security tools in the crypto ecosystem. Startups are already developing AI-powered smart contract auditing platforms that integrate EVMbench-trained models, promising faster, cheaper, and more consistent audits than traditional manual methods. As blockchain adoption grows, so too does the need for scalable, reliable security—making EVMbench not just a benchmark, but a foundational tool for the future of Web3 safety.