AI That Outpaced Hackers: Mythos Finds 'Gaps' Where Millions Have Searched 0 25

Anthropic, a leading developer of artificial intelligence systems, proudly introduced its revolutionary model Claude Mythos. Testing has shown that it significantly surpasses its predecessors in analyzing third-party code, understanding architecture, and identifying vulnerabilities. Each new release of AI models steadily deepens automation in the field of information security.

Claude Mythos detects critical vulnerabilities that have gone unnoticed for decades, eluding both experienced specialists and the most advanced automated scanners. Remarkably, Anthropic claims that Mythos has identified thousands of bugs and 'gaps' in widely used software products, covering all major operating systems and browsers.

As a striking example, the model found a critical bug in the OpenBSD operating system that had remained hidden for a full 27 years. It also uncovered a long-standing vulnerability in a popular video application that automated testing tools had scanned 5 million times without detecting any issues.

News of Anthropic's monumental breakthrough instantly shook the markets, particularly the financial sector, which is traditionally the most sensitive to cyber threats and heavily regulated. The Federal Reserve and the U.S. Department of the Treasury even organized an emergency meeting with representatives of the country's largest banks to discuss their readiness for entirely new types of attacks.

Part of the excitement surrounding the model is explained by the developers' decision to temporarily limit access to it. Currently, only about 40 leading tech companies, including giants like Apple, Amazon, and Microsoft, are using Mythos to detect and eliminate vulnerabilities in critical software products. A breach of these products could affect millions of users worldwide.

Such access restrictions deprive cybercriminals of the ability to use the most advanced model, providing a significant advantage to select players in the global IT industry. These companies have the opportunity to address 'gaps' in widely used services more quickly and significantly enhance their cybersecurity. This seems like a reasonable step: first, thoroughly test the technology in complex real-world conditions, identifying all risks where there are sufficient resources for qualified verification.

At the same time, limited access serves as a powerful marketing tool, fueling interest in the innovative solution. Anthropic ambitiously plans to triple its revenue by 2026, highlighting the commercial potential of Mythos.

The Evolution of Cyberattacks: What Awaits Us

Nowadays, cybercriminals actively use artificial intelligence to automate vulnerability discovery and meticulously prepare their attacks. Typically, they generate an extensive stream of hypotheses, each requiring painstaking manual verification. From the vast number of discovered 'findings,' only a small number of truly dangerous 'gaps' need to be identified, confirmed, and then an effective exploitation chain constructed.

The latest models from Anthropic, such as Mythos and its predecessor Opus 4.6, released in February 2026, are capable of much more. They not only make assumptions but also autonomously build complete exploitation chains: finding, verifying, and utilizing vulnerabilities in a semi-automated or even fully automated mode. In simpler terms, all that is needed is the model itself and a well-crafted prompt.

Mythos has vividly demonstrated an unprecedented level of automation for this complex task. As a result, the time interval between discovering a vulnerability and creating a working attack scenario is reduced so dramatically that AI transforms from a mere assistant into a powerful, fully-fledged tool for offensive cyber operations.

As models like Mythos become increasingly accessible, the number of cyberattacks will inevitably rise. Powerful systems allow for significantly more scenarios to be launched simultaneously, and AI radically reduces the hours of manual work spent on reconnaissance, code analysis, scenario preparation, and action automation.

Even with the high cost of using such advanced models, the overall price of a successful attack is significantly lowered due to incredible speed, scale, and savings on expertise. Consequently, even a mid-level attacker becomes a significantly more dangerous adversary.

At the same time, the complexity of cyber threats is rapidly increasing. Artificial intelligence can detect non-trivial combinations of errors, effectively combine multiple vulnerabilities, and identify critical weak points in both infrastructure and supply chains. The window for adequate response is catastrophically narrowing: now the time from vulnerability discovery to mass exploitation takes not months, but mere days or even hours.

Ordinary users will face a qualitatively new, much more personalized form of social engineering. Fraudulent emails, phone calls, and phishing sites will become incredibly convincing and will be tailored as precisely as possible to each individual.

Changing Roles: Cybersecurity Specialist vs. Hacker

The entry threshold into the 'profession' for cybercriminals is significantly lowering. Whereas deep technical knowledge or access to expensive tools and services was previously required to carry out complex attacks, soon only a basic understanding and a powerful AI model will suffice. This model will be able to guide the perpetrator through the entire attack chain, from reconnaissance to exploitation.

For the average perpetrator, AI becomes a sort of 'senior partner' that effectively compensates for the lack of deep expertise and always suggests the next step. As a result, criminal groups can expand their ranks by recruiting individuals who do not possess unique technical skills but can effectively use AI-based tools.

This trend makes the shadow services market much more mass-oriented and significantly fragmented. At the same time, mirror changes are observed in the profession of cybersecurity engineer, creating new challenges and opportunities.

Novice specialists can now perform higher-level tasks by actively using AI as a powerful learning assistant and indispensable working tool. Neural networks today significantly accelerate the process of understanding code, assist in writing scripts, automate checks, and efficiently analyze vast amounts of event logs.

The ability to work effectively with artificial intelligence is becoming an absolutely basic skill, and the role of the cybersecurity specialist is transforming. It is now shifting from manual searching to overseeing and managing complex systems, where a significant portion of the work is performed by automated agents. For a market suffering from a chronic labor shortage, this is a positive shift: experienced professionals will be able to handle a greater volume of tasks in the same amount of time, while younger employees will achieve high productivity more quickly.

As models continue to improve and the validity of their 'findings' increases, the need for additional manual checks will gradually diminish. However, all these changes represent not so much a revolution as a predictable evolution of the cybersecurity market.

On one hand, artificial intelligence significantly enhances the capabilities of attackers, clearly demonstrating how far automation of vulnerability discovery and exploitation can advance. On the other hand, the same advanced approaches can and must be applied to strengthen defenses.

If the main protection processes in a company are well-structured and maximally automated, it will be able to promptly close discovered 'gaps,' effectively monitor the external attack surface, and quickly respond to any incidents. However, if these processes are absent or merely formal, powerful AI models will only accelerate potential disaster: the number of complex attacks will increase, and the time for adequate response will remain critically short.

Thus, for any business, the conclusion becomes absolutely clear and uncompromising: cybersecurity must be integrated as a managed and measurable function, akin to finance or operational processes. And the construction of this function must begin today, without delay.