The artificial intelligence race has entered a completely different phase. For years, tech companies competed to build faster, smarter and more creative AI models. Now another issue is emerging: what happens when those systems become extremely good at discovering vulnerabilities, automating attacks and working around critical infrastructure.
For the first time, the US government is stepping in before some of those models are publicly released.
This is no longer a theoretical debate. In recent days, it was confirmed that companies including OpenAI, Google, Microsoft and xAI agreed to let US agencies evaluate advanced AI systems before deployment. The focus is on risks tied to cyberattacks, national security, chemical and biological threats and the abuse of powerful automation capabilities.
At the same time, the case of Anthropic and its Claude Mythos Preview model accelerated the discussion even further. Anthropic openly acknowledged that the system had already discovered thousands of severe software vulnerabilities and decided not to release it broadly because of concerns about misuse.
The biggest shift since the AI boom began
Until recently, the process was simple: companies built AI models and then released them to the public. Safety testing existed, but it mostly happened internally.
That is changing fast.
Today, organizations such as the Center for AI Standards and Innovation (CAISI) inside the US Commerce Department are already conducting evaluations on frontier AI systems before launch. These reviews focus on risks involving:
- cybersecurity
- exploit development
- offensive automation
- chemical and biological misuse
- attacks on critical infrastructure
- bypassing safety systems
This marks a major shift. For the first time, the US government is not only observing AI development from the outside — it is becoming directly involved in evaluating models before deployment.
What happened with Anthropic and Claude Mythos
A large part of the current debate revolves around Anthropic.
The company officially confirmed the existence of Claude Mythos Preview, a model developed inside Project Glasswing, an initiative focused on defensive and offensive cybersecurity research.
According to Anthropic’s own documents, the system has already identified thousands of severe vulnerabilities, including flaws affecting operating systems and widely used software. The company also says the model demonstrated the ability to reason about exploit chains and develop complex attack paths with far less human guidance than previous AI systems.
Examples cited by Anthropic include:
- a 27-year-old OpenBSD vulnerability
- a 16-year-old FFmpeg flaw
- Linux privilege-escalation exploit chains
That changed the tone of the global AI conversation. The focus shifted away from “AI writes better” toward something more serious: AI systems capable of finding real weaknesses in critical software.
Why governments are taking this seriously
The concern is not that AI models suddenly “want” to attack systems on their own. The real issue is that they could dramatically lower the technical barrier for advanced cyberattacks.
Until now, discovering serious vulnerabilities required highly specialized teams, deep expertise and long research cycles. But if AI models can review code at scale, detect insecure patterns and suggest exploitation paths, then part of that process becomes automated.
That could affect:
- banks
- hospitals
- power grids
- government systems
- military infrastructure
- telecom networks
- financial services
That is why the conversation has moved far beyond Silicon Valley and into national security discussions.
OpenAI is moving in the same direction
While most public attention focused on Claude Mythos, OpenAI has also started moving into advanced cybersecurity work.
Recent reports indicate that the company has begun providing limited access to GPT-5.5-Cyber, a specialized model intended for government agencies and defensive cybersecurity teams.
In other words, major AI labs are no longer focused only on productivity and chatbots. They are entering offensive and defensive cybersecurity in a much more direct way.
AI companies are accepting pre-release reviews
Another major shift is that the companies themselves are agreeing to government evaluations before launch.
Google DeepMind, Microsoft and xAI agreed to provide early access to advanced models for security-focused testing. OpenAI and Anthropic already had similar partnerships that were later renegotiated under the new US AI strategy.
According to Reuters and other reports, some evaluations involve testing systems with reduced safeguards to better understand real-world risk scenarios.
That matters because it helps officials understand what could happen if attackers bypass safety layers.
The political fight behind the AI boom
At the same time, a political battle is emerging inside the US government.
Some officials want these reviews to remain voluntary. Others are pushing for stricter oversight and possibly mandatory approval systems before certain frontier models can be released.
Meanwhile, intelligence agencies, the Pentagon and civilian regulators are debating who should control these evaluations. The reason is simple: AI is no longer just consumer technology. It now touches defense, espionage, infrastructure and geopolitics.
Why this could change the future of the internet
The rise of systems like Claude Mythos and GPT-5.5-Cyber shows that the next phase of AI is not mainly about image generation or virtual assistants.
The real transformation begins when models can:
- discover real vulnerabilities
- automate offensive analysis
- work directly with critical software
- assist complex security research
That could significantly improve digital defense — but it could also create serious risks if those capabilities spread uncontrollably.
What happens next
For now, the most sensitive models remain under limited and controlled access. But the deeper issue is only beginning.
Every new generation of AI becomes better at:
- coding
- analyzing software
- reasoning about complex systems
- automating technical workflows
That means the line between useful and dangerous technology keeps getting thinner.
Conclusion
The decision to review advanced artificial intelligence systems before public release marks a historic change in the tech industry.
The United States is no longer treating AI as only a commercial innovation. It is beginning to treat it as a technology with direct implications for national security, critical infrastructure and global cybersecurity.
And after cases like Claude Mythos, it is becoming clear why the conversation no longer sounds like science fiction.
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