Why Anthropic’s Mythos Model is a Game Changer for Cybersecurity

Introduction

If you have been in the news lately, you have probably heard about Anthropic’s new model. The name is Mythos. According to them, it is too powerful to be released to the public, so they gathered a team of companies and called it Project Glasswing. I will talk more about them later.

Their job is to make sure the future of software is secured, and I just want to say thank God it was them that found it first and not Google. I love Google, but Google would have released that model behind a paywall, and bad actors all over the world could have used it.

We have been hearing about what Mythos can do, but what is it?

What Is Mythos?

Mythos is a large language model trained for general use. It is not specifically built for cybersecurity or for anyone only in that field, but guess what: it is good at cybersecurity.

The model is good because it is trained on a lot of cybersecurity data, but not only that. It can code, and it has an understanding of different components of operating systems, networking, and browser engineering. This gives it the ability to find zero-day exploits that no one else could have found because no one has all that understanding at once.

An easy way to explain what makes it good is this: imagine having someone who is 8/10 in cybersecurity, but then also an 8 in every other thing around it. That is what Mythos is like.

Because of that, it is not just doing basic attacks like a stack buffer overflow, where you write something into memory outside what an app allocated. It can do complex attacks that require a full understanding of a system. For example, Anthropic said it made an exploit using JIT spraying to escape the renderer and the OS sandbox.

How Good Is the Model?

So knowing all this about the model, I think we can say this model is a beast.

Anything you throw at it, it performs. In SWE-Bench Pro it scored 77.8%. In Terminal-Bench it scored 82.0%. In SWE-Verified it scored 93.3%.

But right now we can mostly test the model’s performance for coding because the model is not public. Still, there are other reasoning benchmarks too. On Humanity’s Last Exam, it scored 56.8%. This is a benchmark that brings out hard questions from every field, and it is graded by industrial experts in each field. So the model getting 56.8% is really good, and that is without tools. With tools, it scored an incredible 64.7%.

There are other things showing it is good for agentic use too.

This are them bench mark scores

Why This Matters for Cybersecurity

The model is really good, I guess, but how can this model kill cybersecurity?

Basically, every time they throw this model at a repo, it finds exploits. This is a list of some of the exploits it found:

• OpenBSD SACK Vulnerability: a 27-year-old remote denial-of-service vulnerability in the OpenBSD implementation of TCP Selective Acknowledgement that allows an attacker to crash any host responding over TCP.
• FreeBSD NFS Remote Code Execution: a 17-year-old vulnerability in the FreeBSD kernel’s NFS server that allows unauthenticated remote attackers to gain full root access.
• FFmpeg H.264 Slice Counter Overflow: a 16-year-old vulnerability in the FFmpeg H.264 codec where an overflow in the slice counter can lead to out-of-bounds heap writes and process crashes.
• Web Browser Exploit Chain: an exploit that chained four separate vulnerabilities together, including a complex JIT heap spray, to escape both the renderer and OS sandboxes.
• Linux Local Privilege Escalation: multiple exploits that chained together vulnerabilities such as subtle race conditions and KASLR bypasses to achieve complete root access on Linux systems.
• Memory-Safe VMM Vulnerability: a memory-corruption vulnerability in a production memory-safe virtual machine monitor that allows a guest to perform an out-of-bounds write to host process memory.
• Firefox JavaScript Shell Exploits: developed working exploits for previously patched vulnerabilities in the Mozilla Firefox 147 JavaScript engine.
• Tier 5 Control Flow Hijacks: achieved full control flow hijacks on ten separate, fully patched open-source repositories from the OSS-Fuzz corpus.
• Additional Codec Vulnerabilities: identified various other vulnerabilities in FFmpeg’s H.264, H.265, and AV1 codecs.

As you can see, the model is good at finding exploits. But according to Anthropic, this is just 1% of the exploits they found, and the remaining ones have not been patched yet, so they cannot tell us for obvious security reasons.

How They Are Handling It

So Anthropic saw the model’s capabilities and called Google, Apple, Cisco, JPMorgan, the Linux Foundation, and many more companies. They called this team Project Glasswing.

This was founded on the idea that if a model like this is going to come out, the world’s infrastructure should be secure and should be able to fix the bugs before bad actors find and use them. The goal is to make sure the world does not get hit by a wave of vulnerabilities before defenders are ready.

And in this, I wish them good luck.

Is the Model Really That Good?

In some testing, the model had some advantages. For example, in the Firefox exploit case, the model was given a version of Firefox without the browser sandbox, and it usually ran in sandboxes that lacked production-level security.

But that does not mean the model is not impressive. The model gave Anthropic engineers who knew nothing about security the ability to find all those exploits. Imagine what it could do in the hands of an actual cybersecurity person. How many more exploits would that person find over the Anthropic engineers?

The model itself also showed some unusual behavior. It would sometimes perform worse during tests, almost as if it knew it was being tested. The model could also try to hide what it was doing in some cases, and it was not always the best at evaluating its own ideas.

What Can We Do Right Now?

I recommend that you update everything to the latest version: your phone, your laptop, your television, your router. If it runs software, update it.

Also check on friends and family to make sure they do the same thing.

Then people should use models that are currently available, like Opus 4.6, Gemini 3.1 Pro, or GPT-5.4 xhigh, to go through repos and check for any security vulnerabilities and fix them. This is a time to put security above anything else.

Conclusion

I do not think you should panic, but I do think you should focus on security and getting better.

You can send me a message on X at @Jemolife69.

And remember: stay coding.