Artificial Analysis 推出 CyberGym-E2E-AA 基准，衡量模型在内存安全任务上从漏洞发现到修补的防御能力，部分前沿模型因安全拦截在 85%+ 任务上无法响应。GPT-6 Luna 或 MiMo-V2.6-Pro 可在 100 万行以上代码库中执行约 100 次漏洞挖掘，成本约 $20，单任务比次优模型 Grok 4.7 便宜最多 100 倍。
Restricting offensive without blocking defensive is difficult, as finding and proving a vulnerability requires the same steps whether the goal is to exploit it or patch it
On CyberGym-E2E-AA, a benchmark that measures cyber defense capabilities from discovery to patching on memory-safety tasks, some frontier intelligence models are safety blocked from responding on 85%+ of tasks.
The good news is that some of the most capable models are also the most cost effective. With GPT-6 Luna or MiMo-V2.6-Pro, you can run ~100 bug hunts in a 1M+ line codebase for ~$20 - up to 100x cheaper per task than the next most capable model Grok 4.7.
来源：Artificial Analysis · x.com