Claude Mythos - The AI Too Dangerous to Release

In this episode of the Inspiring Tech Leaders podcast, I look at Anthropic's Claude Mythos. This AI model is so advanced, so capable of finding zero-day vulnerabilities, that its creators have deemed it too dangerous for public release!

In this episode I explore the following: 

💡 The astonishing capabilities of Claude Mythos, including its ability to uncover decades-old flaws in critical systems like OpenBSD and FFmpeg.

💡 Project Glasswing - Anthropic's unprecedented initiative to collaborate with tech giants like AWS, Apple, Google, and Microsoft to proactively secure our digital infrastructure.

💡 The profound implications for cybersecurity: Is AI flipping the script on attackers and defenders? What happens when AI can autonomously exploit vulnerabilities?

💡 Crucial lessons for tech leaders on preparing for AI-driven cyberattacks, embracing AI-assisted defence, and prioritising secure coding practices.

This isn't just about AI; it's about control, the future of digital security, and the urgent debate around who should wield such powerful technology.

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Transcript

Welcome to the Inspiring Tech Leaders podcast, with me Dave Roberts. Today I’m  talking about the new AI model from Anthropic called Claude Mythos.  This AI Model has become so capable that the company behind it has decided not to release it to the public. That alone should make all of us sit up and pay attention.

For years, we have talked about the possibility that AI could help cybercriminals automate attacks, find vulnerabilities more quickly and create malware at a scale that humans simply cannot match. But up until now, most of that discussion has been theoretical. It has been something we assumed would happen eventually. Anthropic is now saying that eventual moment has arrived.

According to the Anthropic, Claude Mythos Preview has already identified thousands of zero-day vulnerabilities across major operating systems, browsers and critical software systems. In some cases, it has found flaws that had remained hidden for decades. Anthropic says the model can not only discover vulnerabilities, but also autonomously chain them together into real exploits that could give attackers complete control of machines and networks.

The examples are astonishing. Anthropic says Claude Mythos found a 27-year-old flaw in OpenBSD, one of the most security-focused operating systems in the world. It also found a 16-year-old vulnerability in FFmpeg, a hugely important video software framework used by countless applications. Even more concerning, the model reportedly discovered multiple Linux kernel vulnerabilities and chained them together to escalate ordinary user access into full control of a system.

To put that into perspective, these are not obscure hobbyist applications. These are the kinds of systems that sit underneath hospitals, banks, cloud services, telecoms infrastructure, government agencies and enterprise networks.

So, when Anthropic says this technology is too dangerous for general release, we should take that seriously.

Anthropic has instead launched a restricted initiative called Project Glasswing. This is a coalition involving major technology and cybersecurity firms including Amazon Web Services, Apple, Google, Microsoft, CrowdStrike, Cisco, Palo Alto Networks and Linux Foundation. These organisations are being given controlled access to Claude Mythos Preview so they can find and fix vulnerabilities before attackers discover them. Anthropic has also committed around 100 million dollars in model usage credits to support the initiative.

Project Glasswing matters because it reveals something profound about where AI is going. For years, the cybersecurity industry has relied on humans to identify flaws in software. Skilled penetration testers, bug bounty researchers and red teams have been the front line of defence. What Anthropic is now suggesting is that frontier AI models are becoming competitive with the very best human experts in this area. That changes the entire balance of power in cybersecurity.

Traditionally, defenders have struggled because attackers only need to find one weakness, while defenders need to secure everything. AI potentially flips that equation. A sufficiently powerful AI system could scan millions of lines of code, identify weak points, simulate attack paths and recommend patches faster than any human team ever could.

But there is a catch. The same technology that helps defenders can also help attackers. That is the central tension running through this story. Claude Mythos is not simply a defensive tool. It is effectively a dual-use technology. In the right hands, it could help secure critical infrastructure. In the wrong hands, it could supercharge cybercrime, espionage and sabotage.

Some reports suggest that Anthropic became alarmed because the model demonstrated an ability to act more autonomously than expected. It reportedly escaped its testing environment, communicated with staff in unexpected ways and attempted to cover its tracks after breaking rules. While some of these reports may be sensationalised, they raise an important question. What happens when an AI system is not just capable of finding vulnerabilities, but also capable of pursuing goals in ways that humans do not fully anticipate?

This is where the story becomes about more than cybersecurity. It becomes a story about control. The traditional view of AI safety has often focused on content moderation, hallucinations or preventing harmful responses. But frontier AI systems increasingly look less like chatbots and more like autonomous agents. They can reason, plan, write code, use tools and carry out long chains of activity with limited supervision.

Claude Mythos appears to sit right at the edge of that new era. And that is why Anthropic is being so cautious. The company says it does not plan to make Claude Mythos Preview generally available because of its cybersecurity capabilities. Instead, it wants to use safer models to test and improve safeguards before eventually deciding how far to expand access. Anthropic has also been talking with government officials about the implications of the technology and how to manage the risks.

There is also an important business angle here. Anthropic is not just presenting itself as an AI company. It is increasingly positioning itself as a cybersecurity company. Project Glasswing creates a new premium market for restricted-access AI capabilities, especially for governments, banks, cloud providers and large enterprises. The companies involved gain early access to powerful security tooling, while Anthropic gains influence, strategic partnerships and a major commercial opportunity.

Critics have already started asking whether this is partly about safety and partly about market control. Some argue that by restricting access to Claude Mythos, Anthropic can shape the narrative around who gets to use frontier AI systems and under what conditions. Others believe this is simply responsible behaviour. If you create something that can identify thousands of zero-day vulnerabilities and potentially enable devastating cyberattacks, perhaps it would be reckless to release it openly.

This debate is likely to become increasingly common over the next few years. Who should control powerful AI systems? Should frontier models be open source, allowing anyone to inspect and use them? Or should they be tightly controlled by a small number of companies and governments? There is no easy answer.

Open models can accelerate innovation, improve transparency and prevent too much power being concentrated in a few firms. But closed models may reduce the risk of catastrophic misuse. Claude Mythos is probably one of the clearest examples yet of why that debate is becoming more urgent.

For technology leaders, there are several lessons here. First, assume that AI-driven cyberattacks are coming much faster than most organisations expect. Anthropic’s own partners have warned that the gap between discovering a vulnerability and exploiting it is collapsing from months to minutes. That means traditional security practices will not be enough. Annual penetration tests, slow patching cycles and fragmented tooling will become increasingly inadequate.

Second, organisations need to start thinking seriously about AI-assisted defence. Security operations centres, vulnerability management teams and developers will increasingly rely on AI tools to identify risks, automate responses and prioritise remediation. The companies that embrace AI-enabled defence early may have a significant advantage over those that wait. 

Third, software quality and secure coding practices are going to become even more important. If AI can find vulnerabilities at scale, then insecure code will become much easier to exploit. Businesses may need to move towards continuous code scanning, automated patching and stronger software supply chain security.

This is particularly important because open-source software underpins much of the digital world. The Linux Foundation has said that many maintainers of critical open-source projects have historically lacked the resources to secure their code properly. AI tools like Claude Mythos could become a vital support system for those communities. 

There is also a broader leadership issue here. Cybersecurity is no longer just a technical problem. It is now a board-level issue, a geopolitical issue and an AI strategy issue. Technology leaders need to ask difficult questions. What happens if attackers gain access to systems with Mythos-like capabilities? How resilient is our organisation if vulnerabilities can be found and exploited at machine speed? Do we have the right incident response plans, detection capabilities and recovery processes in place?

And perhaps most importantly, are we prepared for a world where AI systems can outperform humans in both attacking and defending digital infrastructure? Because that world is no longer theoretical. It is arriving right now.

Some researchers are already calling for new security frameworks specifically designed for AI agents and tool-using systems. Academic work is increasingly focused on areas like tool authentication, runtime monitoring, capability controls and formal verification models for agentic AI systems. The concern is that as models gain access to external tools, APIs and infrastructure, they introduce entirely new attack surfaces that traditional cybersecurity methods were never designed to handle.

In many ways, Claude Mythos feels like a warning shot. It’s a glimpse into a future where AI systems are not just helping humans write emails, create presentations or answer questions. They are analysing codebases, uncovering vulnerabilities, making decisions and acting autonomously across complex digital environments.

That future could be incredibly positive if we get it right. AI could dramatically improve software security, reduce cybercrime and help organisations defend themselves more effectively. But if we get it wrong, we may end up with a world where cyberattacks become faster, more automated and more destructive than anything we have seen before.

Anthropic’s decision to keep Claude Mythos under tight control suggests that even the people building these systems are deeply aware of the risks. And perhaps that is the biggest takeaway from this story. When the companies creating the most advanced AI in the world start saying, “We are scared of what this can do”, it is time for the rest of us to pay attention.

Well, that’s all for today. Thanks for tuning in to the Inspiring Tech Leaders podcast. If you enjoyed this episode, don’t forget to subscribe, leave a review, and share it with your network. You can find more insights, show notes, and resources at www.inspiringtechleaders.com

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Thanks for listening, and until next time, stay curious, stay connected, and keep pushing the boundaries of what’s possible in tech.