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OpenAI sharpens AI race for cyber defence

OpenAI has launched GPT-5.4-Cyber, a new version of its frontier model tailored for defensive cybersecurity work, moving quickly to answer growing concern that ever more capable AI systems could help both defenders and attackers in a widening digital arms race. The release came a week after Anthropic disclosed Claude Mythos Preview under its tightly controlled Project Glasswing programme, setting up a new contest over who can best position advanced AI as a shield rather than a threat.

OpenAI said the model would be rolled out first to vetted security researchers, organisations and defenders rather than the wider public. The company is expanding its Trusted Access for Cyber programme, launched in February, with additional verification tiers that give authenticated defenders broader access to more cyber-permissive capabilities. At the highest levels, users can work with GPT-5.4-Cyber with fewer restrictions for tasks such as vulnerability research, cyber threat analysis and defensive testing.

That measured release reflects the central tension now shaping the cyber segment of the AI industry. Companies argue that stronger models can help identify software flaws faster, improve incident response, sift huge volumes of threat intelligence and reduce the workload on overstretched security teams. At the same time, regulators, banks and security specialists are weighing how quickly those same systems might lower the barrier for misuse if they are allowed to operate with too few safeguards. Reuters reported this week that European Central Bank supervisors are preparing to question banks about the risks linked to Anthropic’s Mythos model, underscoring how quickly the issue has moved from laboratories to financial oversight.

Anthropic’s move earlier this month sharpened that debate. The company said Claude Mythos Preview would not be made generally available and instead would be shared with a small set of partners including large technology groups, cybersecurity vendors and JPMorgan Chase through Project Glasswing. Anthropic said the model would be used to find and fix weaknesses in core software and infrastructure that make up a large share of the global attack surface, including endpoints, binaries and foundational systems.

OpenAI’s answer is notable not just because of timing, but because it suggests the leading AI developers are converging on a new operating model for high-risk cyber capabilities: restricted access, identity checks and tiered permissions rather than open release. That is a departure from the broader software industry habit of scaling tools as widely and as quickly as possible. OpenAI has framed GPT-5.4-Cyber as a purpose-built defensive system, not a general public chatbot with marginal extra cyber skills. The company’s official material says the model has been fine-tuned for cybersecurity and made available through a trust-based access framework designed to widen defender access while preserving safeguards.

The launch also fits a broader strategic push by OpenAI to build specialised tools around GPT-5.4, which the company introduced in March as its flagship frontier model for professional work. In the weeks that followed, it also unveiled Codex Security, an application security agent that can analyse project context, identify vulnerabilities and propose patches. Together, those releases show that cybersecurity is becoming an increasingly important commercial and policy battleground for frontier AI firms, particularly as enterprise buyers look for practical uses beyond content generation and customer service.

For defenders, the promise is obvious. Large models can accelerate code review, prioritise alerts, simulate attack paths and help security teams triage incidents with far greater speed than human-only workflows. For vendors, they also create a new market in premium, tightly governed tools for governments, financial institutions and critical infrastructure operators. Yet the industry still faces a credibility test. Claims about models discovering major vulnerabilities at scale are difficult to verify publicly when access is restricted, and some outside observers have questioned whether companies are mixing genuine safety concerns with competitive positioning and publicity.



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