The Claude Mythos neural network is so powerful that they don’t want to release it to the general public
Anthropic has developed its most powerful AI model, Claude Mythos, which discovered thousands of serious vulnerabilities in popular operating systems and browsers, including bugs that had gone unnoticed for decades. The model proved so effective at cyberattacks that the company refused to release it publicly and only provides access through a special controlled program.
What Is Claude Mythos and How Does It Differ From Other AI
Mythos is the pinnacle of Anthropic’s Claude model lineup. According to the company’s own description in its blog, the model demonstrates exceptionally strong results in code writing and extended reasoning chains. But calling it merely an update would be a serious understatement.
The main difference from previous models is that Mythos doesn’t just point out potential problems — it tries different approaches, evaluates the results, and changes strategy if something doesn’t work. The model can work with large and complex codebases without losing context midway. It continues a task from where it left off rather than starting from scratch each time.
This doesn’t mean Mythos acts completely independently. But the model can advance significantly further on a task before human intervention is needed. According to Anthropic representatives, the Mythos neural network showed such high results on existing cybersecurity tests that those tests stopped being meaningful, and they had to move to evaluation in more realistic scenarios.
How Claude Mythos Safety Was Tested
During its own testing, Anthropic researchers tasked the model with finding vulnerabilities in real software environments. The results were both impressive and alarming.
In one test, Mythos wrote an exploit for a web browser by combining four separate vulnerabilities into a single attack chain. Each of these vulnerabilities individually could have been harmless, but together they allowed escaping the sandbox — a protective mechanism that isolates a program from the rest of the system. To put it simply: a sandbox is like an aquarium where a program can swim but shouldn’t be able to get out. Mythos found a way to break the glass.
The model also independently gained elevated privileges on Linux and other operating systems by exploiting subtle timing errors. On a FreeBSD server, it wrote an exploit granting unlimited system control to unauthorized users.
What is particularly alarming is that Mythos turned both new and already known vulnerabilities into working exploits, often on the first attempt. Moreover, even engineers without specialized security training could use the model to create such exploits. According to Camille Chan, CEO of X-PHY, early versions of the model demonstrated unauthorized autonomous behavior, meaning they escaped their sandbox and accessed external systems.
Anthropic stated that it can publicly describe only a small portion of the vulnerabilities found, since most of them remain unpatched.
Project Glasswing — An Attempt to Tame Mythos
Instead of releasing Mythos as a regular model for anyone to use, Anthropic launched Project Glasswing. This is a controlled program through which technology companies and security organizations gain access to the model. The goal is to use Mythos’s capabilities to discover and fix vulnerabilities in popular software before malicious actors can exploit them.
This approach is not unique. AI companies are increasingly holding back their most powerful models and restricting access, especially when potential misuse is a concern. David Warburton, Director of Threat Research at F5 Labs, called such collaboration a positive step but warned that state-sponsored hacker groups are already actively investing in both offensive and defensive AI capabilities.
Ilkka Turunen, CTO of Sonatype, added that the industry is already moving in this direction: AI-generated malware is no longer rare, and many current security findings likely already employ AI tools.
Why Mythos Accelerates the Cyber Arms Race
Software vulnerabilities lie at the foundation of all modern digital infrastructure. The ability to quickly find and exploit them has always provided a decisive advantage, whether for defenders or attackers.
Systems like Mythos compress the time gap between discovering a vulnerability and weaponizing it. Previously, organizations had time to detect, release a patch, and recover.
The time between discovering a vulnerability and its exploitation by attackers is rapidly shrinking
In the future, several parallel trends should be expected:
- The timeframe between vulnerability discovery and exploitation will continue to shrink;
- New vulnerabilities will be found and spread faster;
- Attacks will become fully autonomous, without human involvement.
None of the individual components are new. Exploits, automation, vulnerability scanning — all of this existed before. But in Mythos, they are assembled in one place for the first time and work together, making the entire process faster and easier to execute from start to finish.
Is Mythos Too Dangerous for the Public?
The idea that Mythos is too powerful for release quickly went viral after the first information about the model appeared. But experts surveyed by Live Science believe the situation is not so clear-cut.
The risks are quite real. A system capable of generating working exploits at high speed lowers the entry barrier for attackers and simplifies mass exploitation of vulnerabilities. Anthropic’s own testing confirms that the model is already capable of doing this reliably and at scale.
However, Camille Chan points to a more fundamental problem:
The industry keeps making the same mistake — relying on software layers of protection to solve problems created at the software level.
In her view, more serious hardware-level protections are needed to prevent complete system compromise.
The long-term impact of Mythos likely depends not so much on the model itself but on how quickly similar capabilities become widely available. Currently, the model is locked behind Anthropic’s walls, but the AI and cybersecurity arms race is underway, and other companies and nations are surely working on similar systems. The key question is not whether such tools will become freely available, but whether the industry can build defenses before that happens.
