Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

What began as reports about Anthropic’s Mythos model has now moved into a gated research preview called Mythos Preview. For cybersecurity, that immediately raises an important question: what happens when advanced AI can accelerate offensive workflows such as vulnerability analysis, exploit development, and attack planning? In a recent Cato blog post, we addressed the broader strategic shift this represents.

Gartner published the inaugural Hype Cycle for Agentic AI last week (and yes, we’re included in two subcategories - Agentic AI Security and Guardian Agent). A few things worth noting. It's inaugural, Gartner publishes over 130 Hype Cycles a year, and standing up a new one signals that a space has earned its own map. And it dropped in April, months ahead of the June - August window when these things usually appear.

A CVE surfaces in the morning. By the time you are talking to that customer, you can tell them: we saw it, we checked your environment, you were not affected, and we deployed a rule that will catch it if it ever shows up. For MSSPs and MDR providers, detection engineering is among the most valuable services you can offer. It is also among the most expensive to deliver consistently and at scale.

It was a bold move, but our finance team was fully on board. They both approved and championed the approach. They wanted to see exactly how much value we could unlock for our customers. They didn't look at the resulting bill and ask us to slow down.

RAG systems connect AI models to your internal data, making them powerful but also creating serious security gaps in access control, data retrieval, and compliance. Knowing how to ensure data security in RAG systems means securing every layer of the pipeline from ingestion to retrieval to output.

The question circling boardrooms and compliance departments in 2026 is no longer hypothetical: Can AI replace a QSA? After nearly two decades guiding organizations through PCI DSS audits, gap assessments, and remediation programs, the answer is clear — No, AI cannot replace a Qualified Security Assessor in 2026. But it is fundamentally reshaping what being a QSA means, and professionals who ignore that shift do so at their own peril.

Anthropic’s Project Glasswing and the Claude Mythos model represents a fundamental change in the physics of cyber defense. With the gap between patch releases and weaponized exploits shrinking to hours, traditional manual security triage is now obsolete. Organizations must adopt AI-driven automated remediation.

In the fifth installment of SafeBreach’s AI-First series, VP of Development Yossi Attas explores how the development team’s AI-First philosophy is being extended to the customer frontier and improved upon through the Anti-Hallucination Protocol.

Anthropic just released Claude Mythos Preview. They did not make it publicly available. That decision alone should tell you everything you need to know about what this model can do. During internal testing, Mythos autonomously discovered and exploited zero-day vulnerabilities across every major operating system and web browser. It found a 27-year-old bug in OpenBSD. A 16-year-old vulnerability in a widely used media codec.

The revolution is here, but it’s not what we expected. AI coding assistants have transformed software development, with developers shipping code faster than ever before. GitHub Copilot, Amazon CodeWhisperer, and Claude Code have become as essential to modern development as Git itself. The productivity gains are undeniable; what once took hours now takes minutes. But there’s a dangerous blind spot in this revolution: security.