Organisations face a new risk, not in the fundamental nature of security, but in the speed at which vulnerabilities are exposed. Last month, Anthropic announced Claude Mythos, an AI security tool so powerful, the company said, that it could only release it to a handful of trusted organisations.

The security industry reacted accordingly: the respective National Cyber Security Centres in Ireland and the UK both published useful assessments. The Cloud Security Alliance rallied a stellar cast of contributors to produce a briefing for security leaders. The UK AI Security Institute also had a clear-eyed evaluation of Mythos’ abilities.

The story got mainstream attention beyond industry circles. In light of the news that AI could potentially highlight threats before defenders have the chance to identify the risks, the Irish Times questioned the vulnerability of financial institutions, as did Reuters’ report on US banks. For the public, the BBC’s cyber reporter Joe Tidy had a balanced and hype-free explainer piece.

That’s the context; now here’s the question: does Anthropic Mythos pose a tangible threat to organisations? In this blog, we’ll cover steps that organisations can take to proactively defend against and respond to a new class of AI-enabled security threats.

Defining Mythos and its Capabilities

Mythos enhances software engineering capabilities for code generation and understands how components interact across a codebase. The AI model can also identify subtle bugs and rapidly discover vulnerabilities, scanning code for security flaws at greater speed and accuracy than manual code review or traditional static analysis tools. However, the flipside is that cybercriminals could also use this AI model to exploit system vulnerabilities.

In addition to Mythos, comparable products like Google’s Big Sleep, OpenAI’s GPT-5.4-Cyber, and Aisle demonstrate the emergence of a new class of AI-enabled security assets. These advancements show that computing capacity, rather than human cognitive capability, now determines how quickly hardware and software vulnerabilities are found and fixed.

How Real is the Risk?

Now that Mythos’ code analysis can identify low-level vulnerabilities that would have gone unnoticed for years much faster than ever, traditional manual defence methods are becoming outdated. As a result, the grace period that defenders once had to address vulnerabilities before they were exploited is no longer possible.

A lack of investment in cybersecurity resources (such as people, processes, and technology) creates deep underlying weaknesses that AI-enabled attacks could expose. In particular, technical debt such as unpatched or poorly coded systems face the risk of rapid exposure. As the NCSC UK Director recently pointed out, legacy technology must no longer be viewed as just a mere financial line item, but as a critical operational liability that will be the first target for AI-driven discovery.

Practical Steps for Cybersecurity Programmes

Evolving from static security models to AI responsive frameworks is now a business imperative. This shift requires organisations to adopt a model of accelerated disclosure, where the time between a patch being issued and an adversary attempting to exploit the underlying flaw is measured in hours, not weeks. As the remediation window continues to shrink, cybersecurity programmes must prioritise operational discipline over occasional compliance. The following steps should guide immediate action:

1. Update asset inventories – Full visibility across all environments is necessary, as you cannot protect what you cannot see.
2. Establish a vulnerability management process – Formalise a proactive process for identifying, disclosing and remediating flaws in acquired or developed systems and networks. Defensively scan for vulnerabilities and implement 24/7 monitoring for anomalous behaviour.
3. Prioritise patching – The shrinking remediation window demands that critical patches are deployed quickly. Use risk based prioritisation to determine patch urgency. Where patching is not possible, such as with operational technology, focus on implementing compensating controls e.g. network segmentation, security monitoring, and restrictions on Internet facing exposure.
4. Implement secure coding – Insecure, manual, or poorly documented code increases the attack surface. Evaluate development practices, as well as those of suppliers, to ensure that code is clean, well documented, and secure technical configurations are in place. Automating security testing where possible, provides easily repeatable and scalable security measures.
5. Risk management – Assess risk exposure to unsupported system components and update risk assessments and risk registers to include AI specific risks, as well as vulnerabilities in third-party supply chains.

As well as these tactical steps, strategic resilience relies on continuously engaging with Ireland and the UK’s National Cyber Security Centre advisories and the Cyber Fundamentals (CyFun) framework. Security leaders and professionals should treat Mythos and other AI tools as part of other broader risks such as geopolitics and supply chain risk. For organisations, this means building a defence that is not just reactive, but structurally prepared for a world of autonomous discovery.

A Catalyst for Action

The introduction of Mythos presents a tangible threat through the rapid increase in exposure, but it also offers organisations the chance to modernise their defences. The current strategic window provides the opportunity to use vendor-led patching and restricted AI tools to harden our environments before the threat landscape becomes even more accessible. The imperative for organisations is to treat this development as a catalyst for rigorous operational discipline.

What is clear is that the era of allowing outdated technology to persist has ended, as these technologies pose the greatest operational risks for organisations. It’s imperative to replace technical debt with secure by design alternatives and maintain a posture of continuous monitoring. In an environment where vulnerabilities are discovered at machine speed, resilience will be defined by our ability to take action and to close the window of opportunity for adversaries.

Reasons to be Cheerful?

For any technology and security teams worried about the scale of the task facing them, let’s wrap up on an optimistic note. One of the organisations invited to Project Glasswing was Mozilla, whose release of Firefox 150 included fixes for no less than 271 vulnerabilities that it identified using Mythos. The browser maker published an excellent and reassuring blog post. Mozilla’s Bobby Holley wrote: “You may need to reprioritise everything else to bring relentless and single-minded focus to the task, but there is light at the end of the tunnel… Of the bugs found by Mozilla, there’s none that couldn’t have been found by a competent security professional.”

Author: Sarah Hipkin is a senior consultant with BH Consulting.