APREX · EST. 2026
Anthropic's new large language model, known by its working name Mythos, has sent ripples through the security community. The model is described by both enthusiasts and critics as potentially groundbreaking — and according to Wired, fears of misuse are already widespread. But those who follow the field closely say the real challenge is not about any single model.
A Wake-Up Call for the Entire Industry
According to Wired, there is broad consensus among security experts that the arrival of Mythos should above all serve as a wake-up call for AI developers who have long prioritized functionality over security. The argument is not new, but it carries renewed weight in the face of increasingly powerful models.
The underlying problem is structural: security work has traditionally entered the development cycle late — if it has entered at all.
The real risk is not one model — it is an entire ecosystem of AI tools built without security at the core.
The Market Is Growing — But So Are the Threats
The numbers paint an ambiguous picture. AI-powered defense solutions are expanding rapidly, but attackers are exploiting the same tools.
According to market analyses, the sector is growing at an annual rate of more than 24 percent. At the same time, CrowdStrike's 2024 Global Threat Report documents that the share of malware-free attacks — where traditional antivirus solutions often fall short — rose from 71 percent in 2022 to 75 percent in 2023. SlashNext's 2024 phishing report shows even more dramatic figures: total phishing volume climbed 202 percent, while credential phishing — attacks targeting login credentials — surged by 703 percent in the second half of last year.
Defense and Offense in the Same Toolbox
The dual nature of powerful AI models is at the heart of the debate. On one side, AI gives defenders the ability to analyze vast amounts of data, detect anomalies, and respond to threats far faster than humans alone can manage. IBM's 2024 report shows that organizations actively using AI and automation in their security operations reduced the average cost of a data breach by $2.2 million compared with organizations without such technology — and they were able to contain the damage 127 days faster.
On the other side, AI lowers the barrier for threat actors with limited technical backgrounds to carry out sophisticated operations. CrowdStrike's chief security officer Shawn Henry has noted that AI gives criminals "a new weapon" that makes advanced hacking accessible to a far wider pool of actors, according to research sources in the field.
Generative AI: From Experiment to Mainstream
In 2024, generative AI moved from pilot projects to real-world deployment across many organizations. Within security operations, this has meant that analysts can ask questions in plain English and receive meaningful analysis in return — rather than manually sifting through logs.
Gartner, however, placed generative AI at the peak of the "inflated expectations" curve in its 2024 Hype Cycle report, with analyst Arun Chandrasekaran warning that some degree of disillusionment is inevitable. An ISC2 survey from February 2024 found that 88 percent of security professionals already notice AI affecting their work, while 56 percent believe the technology will make parts of their role redundant.
Structural Weakness at the Core
What the Mythos debate is really exposing, according to Wired, is that AI models themselves can be vulnerable targets — not just tools for attack. Decision-making processes are often opaque, and weaknesses in the models can be exploited in ways developers did not anticipate.
The question the industry now faces is whether Mythos and models of similar caliber will serve as the necessary catalyst to force a genuine security shift — or whether history will repeat itself, and security will once again be pushed to the bottom of the priority list.