OpenAI Launches EVMbench, a New AI Benchmark for Evaluating Smart‑Contract Security
February 18 2026 – The DeFi ecosystem gains a fresh tool designed to measure how well artificial‑intelligence agents can locate, remediate, and even exploit flaws in Ethereum smart contracts.
What is EVMbench?
OpenAI has introduced EVMbench, a benchmarking suite built in partnership with the venture firm Paradigm. The platform assesses the competence of AI models—particularly those geared toward code generation and analysis—in handling vulnerabilities that arise in Ethereum Virtual Machine (EVM) environments.
The benchmark draws on a curated set of 120 historical security issues that were uncovered in more than 40 independent audits. These cases span a range of defect types, from re‑entrancy and arithmetic bugs to permission‑related flaws. Some of the scenarios were contributed by Tempo L1, a project that emphasizes payment‑oriented smart‑contract testing.
EVMbench runs the tests on a Rust‑based harness, providing a deterministic and high‑performance execution environment for each vulnerability case. By feeding the same inputs to different AI agents, the suite produces comparable performance metrics across detection, patching, and exploitation tasks.
Early Results: GPT‑5.3‑Codex
In its first public run, OpenAI evaluated its own model GPT‑5.3‑Codex. The model achieved a 72.2 % success rate when tasked with exploiting the benchmark contracts—a figure that, according to OpenAI, represents a notable improvement over previous iterations.
The results are broken down into three evaluation modes:
| Mode | Description | Score |
|---|---|---|
| Detect | Identify the presence and nature of a vulnerability | – |
| Patch | Generate a corrective code snippet that eliminates the flaw | – |
| Exploit | Produce a proof‑of‑concept attack that demonstrates the vulnerability | 72.2 % |
(OpenAI has not released the detection and patching scores at this stage.)
Why This Matters for DeFi
The DeFi sector has long grappled with high‑profile smart‑contract exploits that have resulted in billions of dollars of losses. As the complexity of decentralized applications grows, manual audits alone are increasingly insufficient. Automation—particularly AI‑driven analysis—offers a promising avenue for scaling security efforts.
EVMbench aims to:
- Standardize AI security assessments: By providing a common set of test cases, developers and auditors can objectively compare the capabilities of different AI tools.
- Accelerate vulnerability discovery: High‑performing models could be integrated into continuous integration pipelines, flagging issues before contracts are deployed.
- Inform model improvement: Detailed benchmark results give AI researchers concrete data on where their systems succeed or fall short, guiding future training efforts.
Paradigm’s Role
Paradigm’s involvement goes beyond sponsorship. The firm contributes domain expertise and quality‑control oversight, ensuring that the vulnerabilities selected for the benchmark are representative of real‑world threats. Their audit experience also helps verify that the benchmark’s outcomes are reliable and reproducible.
Analyst Takeaways
| Insight | Implication |
|---|---|
| AI can now be quantitatively measured in smart‑contract security | Projects can benchmark AI tools against a shared yardstick, reducing reliance on anecdotal claims. |
| Current AI models still miss nearly 30 % of exploit scenarios | There remains substantial room for improvement before AI can be trusted as a sole line of defense. |
| Collaboration between AI labs and crypto expertise is critical | Partnerships like OpenAI‑Paradigm bridge the gap between cutting‑edge ML research and practical DeFi security needs. |
| EVMbench may become a de‑facto standard for AI security audits | As more firms adopt the tool, it could influence how auditors certify contracts and how insurance products assess risk. |
Looking Ahead
OpenAI plans to expand the benchmark with additional vulnerability categories, such as cross‑chain attack vectors and emerging layer‑2 solutions. The company also hinted at future releases of open‑source evaluation scripts, enabling the broader community to contribute new test cases and refine the scoring methodology.
For DeFi developers and auditors, the arrival of EVMbench signals a shift toward more data‑driven security practices. While AI is not yet a silver bullet, its measured integration—backed by transparent benchmarks—could become a cornerstone of the next generation of decentralized finance infrastructure.
The article was produced with assistance from AI‑driven editorial workflows.
Source: https://thedefiant.io/news/blockchains/openai-unveils-ai-benchmark-tool-to-enhance-blockchain-security
