EVMbench draws on 120 curated vulnerabilities from 40 audits, most sourced from open audit competitions such as Code4rena, according to an OpenAI blog post. It also includes scenarios from the security auditing process for Tempo, Stripe's purpose-built layer-1 blockchain focused on high-throughput, low-cost stablecoin payments.
Payments giant Stripe launched the public testnet for Tempo in December, saying at the time that it was being built with input from Visa, Shopify, and OpenAI, among others.
The goal is to ground testing in economically meaningful, real-world code—particularly as AI-driven stablecoin payments expand, the firm added.
Introducing EVMbench—a new benchmark that measures how well AI agents can detect, exploit, and patch high-severity smart contract vulnerabilities. https://t.co/op5zufgAGH
— OpenAI (@OpenAI) February 18, 2026
EVMbench is meant to evaluate AI models across three modes: Detect, patch, and exploit. In “detect,” agents audit repositories and are scored on their recall of ground-truth vulnerabilities. In “patch,” agents must eliminate vulnerabilities without breaking intended functionality. Finally, in the “exploit” phase, agents attempt end-to-end fund-draining attacks in a sandboxed blockchain environment, with grading performed via deterministic transaction replay.
In exploit mode, GPT-5.3-Codex running via OpenAI's Codex CLI achieved a score of 72.2%, compared to 31.9% for GPT-5, which was released six months earlier. Performance was weaker in the detect and patch tasks, where agents sometimes failed to audit exhaustively or struggled to preserve full contract functionality.
The ChatGPT makers' researchers cautioned that EVMbench does not fully capture real-world security complexity. Still, they added that measuring AI performance in economically relevant environments is critical as models become powerful tools for both attackers and defenders.
Sam Altman's OpenAI and Ethereum co-founder Vitalik Buterin have previously been at odds over the pace of AI development.
In January 2025, Altman said that his firm was "confident we know how to build AGI as we have traditionally understood it." But Buterin advocated that AI systems should include a "soft pause" capability that could temporarily restrict industrial-scale AI operations if warning signs emerge.