Strengthening cyber resilience as AI capabilities advance

Cyber capabilities in AI models are advancing rapidly, bringing meaningful benefits for cyberdefense as well as new dual-use risks that must be managed carefully. For example, capabilities assessed through capture-the-flag (CTF) challenges have improved from 27% on GPT‑5⁠(opens in a new window) in August 2025 to 76% on GPT‑5.1‑Codex‑Max⁠(opens in a new window) in November 2025.

We expect that upcoming AI models will continue on this trajectory; in preparation, we are planning and evaluating as though each new model could reach ‘High’ levels of cybersecurity capability, as measured by our Preparedness Framework⁠(opens in a new window). By this, we mean models that can either develop working zero-day remote exploits against well-defended systems, or meaningfully assist with complex, stealthy enterprise or industrial intrusion operations aimed at real-world effects. This post explains how we think about safeguards for models that reach these levels of capability, and ensure they meaningfully help defenders while limiting misuse.

As these capabilities advance, OpenAI is investing in strengthening our models for defensive cybersecurity tasks and creating tools that enable defenders to more easily perform workflows such as auditing code and patching vulnerabilities. Our goal is for our models and products to bring significant advantages for defenders, who are often outnumbered and under-resourced.

We see this work not as a one-time effort, but as a sustained, long-term investment in giving defenders an advantage and continually strengthening the security posture of the critical infrastructure across the broader ecosystem.

Mitigating malicious uses

Building on this foundation:

Ecosystem initiatives to strengthen cyber resilience 

Alongside these collaborations, we are establishing a set of efforts designed to help defenders move faster, ground our safeguards in real-world needs, and accelerate responsible remediation at scale.