# CWE-Bench

> An external benchmark for evaluating whether coding agents can produce correct patches for real-world software vulnerabilities.

Canonical page: https://benchlm.ai/benchmarks/cwebench

- Category: [Agentic](/agentic)
- Last updated: October 17, 2026

## About CWE-Bench

- Year: 2026
- Tasks: Real-world vulnerability patching tasks
- Format: Pass@1
- Difficulty: Automated vulnerability remediation
- Paper: [CWE-Bench leaderboard](https://cwe-bench.com/#leaderboard)

CWE-Bench evaluates automated vulnerability patching. BenchLM stores exact provider-reported pass@1 results as display-only cybersecurity evidence until a stable benchmark-owned result artifact is available for the exact model setup.

CWE-Bench is currently displayed on BenchLM for reference, but it is excluded from the weighted scoring formula.

## Leaderboard (1 models)

| Rank | Model | Creator | Score |
|------|-------|---------|-------|
| 1 | [Gemini 3.8 Flash Cyber](/models/gemini-3-8-flash-cyber) | Google | 47.2% |

## FAQ

### What does CWE-Bench measure?

An external benchmark for evaluating whether coding agents can produce correct patches for real-world software vulnerabilities.

### Which model scores highest on CWE-Bench?

Gemini 3.8 Flash Cyber by Google currently leads with a score of 47.2% on CWE-Bench.

### How many models are evaluated on CWE-Bench?

1 AI models have published results on CWE-Bench in the BenchLM catalog.

### Does CWE-Bench affect BenchLM's overall score?

Not directly. CWE-Bench is still displayed on BenchLM for reference, but it is excluded from the weighted scoring formula.