Goldman Sachs is taking a cautious approach toward a new artificial intelligence model from Anthropic, warning that its advanced capabilities could introduce significant cybersecurity risks—even as they explore its long-term potential.
The model, known as “Mythos,” has sparked concern across the financial sector due to its ability to identify and exploit software vulnerabilities at a level that could reshape both cyber defense and cybercrime.
“Hyperaware” of AI-Driven Cyber Risks
Answering a query during a recent earnings call, Goldman Sachs CEO David Solomon said the bank is closely monitoring the risks associated with emerging AI systems including LLMs and the disruptive Mythos model from Anthropic.
“We’re hyperaware,” Solomon said, referring to the cybersecurity implications of next-generation AI tools.
He added that Goldman is actively working with Anthropic and cybersecurity partners to better understand how such models could impact financial systems and cyber defenses.
Cybersecurity has long been at the core of our business. And we have for a very, very long time, put enormous resources forward,” Solomon added.
“With the help of the US government and the model publishers, we are very focused on supplementing our cyber and infrastructure resilience,” he said. “And this is part of our ongoing capabilities that we have been investing in and are accelerating our investment in.”
The comments reflect the current mindset of major financial institutions, which are increasingly treating advanced AI not just as a productivity tool, but as a potential security disruptor.
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Why Mythos is Raising Concerns
Unlike earlier AI systems, Mythos is designed to autonomously discover and exploit vulnerabilities in software environments. Anthropic has acknowledged that the model can “find and exploit sophisticated vulnerabilities” and, in some cases, outperform human experts.
This capability has triggered concern among cybersecurity community, who are divided and warn that such tools could lower the barrier for cyberattacks. In practical terms, even individuals without deep technical expertise could potentially use AI to identify weaknesses in operating systems, applications, or enterprise infrastructure.
Anthropic itself has taken an unusually cautious stance. The company has restricted access to Mythos and opted not to release it publicly, citing fears of misuse.
Instead, the model is being shared as a preview to 11 organizations under a controlled initiative dubbed “Project Glasswing.” The organizations includes JPMorgan, Apple, Google, Microsoft, Nvidia and Goldman Sachs, among other. The initiative aims at strengthening defenses before rolling out wider deployment.
Financial Sector on High Alert
The concerns are not limited to Goldman Sachs. Discussions involving top U.S. financial leaders—including regulators and central banking officials—have reportedly taken place to assess the risks posed by such AI systems.
Banks are particularly vulnerable due to their complex mix of modern and legacy systems, which could provide fertile ground for AI-driven vulnerability discovery and exploitation.
At the same time, industry leaders see a dual-edged reality where attackers could benefit first, defenders may eventually use similar tools to identify and patch weaknesses faster.
Balancing Risk and Opportunity
Despite the warnings, Solomon struck a measured tone about the future of AI in business. He noted that the technology has the potential to significantly improve efficiency and transform operations across industries.
“Whenever you have acceleration of your technology, there are going to be be bumps, and there are going to be risk issues,” Solomon said answering a seperate query during the call. “But the power of the technology, the ability to use it in an enterprise, to remake processes, to create efficiency, and also create more capacity to invest the growth — I can’t find a CEO that’s not talking about that.”
This tension—between innovation and risk—sits at the center of the current debate around advanced AI systems like Mythos.
A Turning Point for Cybersecurity
The emergence of models capable of autonomously identifying and exploiting vulnerabilities marks a potential inflection point for cybersecurity.
Experts suggest that the rapid evolution of AI could accelerate both offensive and defensive capabilities, creating a race between attackers and defenders. In the short term, however, the concern is that powerful tools may be easier to weaponize than to secure.
For financial institutions like Goldman Sachs, however, the strategy seems to be to engage early, understand the risks, and prepare defenses before such technologies become widely accessible.
