Ethereum gains EVMbench as OpenAI, Paradigm launch benchmark

What to Know:

• OpenAI and Paradigm launch EVMbench for smart contract security benchmarking.
• Benchmarks AI agents detecting, fixing, and safely exploiting Ethereum contract bugs.

OpenAI and Paradigm have launched EVMbench, a benchmark to evaluate whether AI agents can find, fix, and safely exploit bugs in Ethereum smart contracts. The focus is on testing coding, reasoning, and execution in realistic, onchain-adjacent conditions.

The main entity, EVMbench AI bug finder, targets practical questions auditors and developers face before deployment. The launch places AI capability measurement directly within the Ethereum ecosystem’s security workflow.

Why EVMbench matters now: detect, patch, and exploit capabilities

EVMbench organizes tasks across three modes, detect, patch, and exploit, to assess end-to-end capability. As reported by The Block, OpenAI frames the work as benchmarking models in “economically meaningful environments” to advance defensive uses.

Results matter for operational risk management because exploit proficiency may outpace safe detection and remediation. As reported by Investing.com, community commentary notes rapid gains in “exploit” performance, from roughly 32% with a prior model to about 72% with GPT-5.3-Codex, alongside persistent gaps in “detect” and “patch.”

“with $100B+ in assets sitting in open source crypto contracts, there’s a real risk from AI agents capable of finding exploits. EVMbench is designed to measure what agents can do , in detecting, patching, and exploiting vulnerabilities,” said Alpin Yukseloglu, a partner.

Based on data from arXiv, recent studies indicate LLM-assisted tools are beginning to outperform many traditional auditing tools in controlled setups, while edge-case logic flaws remain challenging. This pattern suggests benchmarks that emphasize real-world constraints can complement human review.

How EVMbench works: real audits, containerized sandbox, answer keys

According to Paradigm, EVMbench draws on real vulnerabilities from about 40 audits, plus custom unreleased contract tasks. Agents run inside containerized sandboxes, and each task has an answer key to ensure solvability and objective scoring.

This design aims to make results reproducible while constraining real-world risk: tasks are solvable, execution is isolated, and content is sourced from authentic audits to reduce gaming. The approach supports apples-to-apples comparisons across models and versions over time.

At the time of this writing, Coinbase Global (COIN) traded near $168.78, up 2.71% intraday, based on data from NasdaqGS. This provides market background and does not affect the technical scope or findings of EVMbench.