Identifying Vulnerabilities and Exploits with Claude Mythos Preview
In recent weeks, the Claude Mythos Preview has proven invaluable in uncovering a multitude of previously unknown zero-day vulnerabilities—software flaws that had not been recognized by their developers. These findings cover critical issues across major operating systems, web browsers, and various other essential software applications.
An in-depth post on our Frontier Red Team blog shares technical insights on select vulnerabilities that have been addressed, including methods that Mythos Preview employed to exploit them. Remarkably, it was able to autonomously identify nearly all of these vulnerabilities and develop exploits without any human intervention. Here are three notable examples:
- Mythos Preview uncovered a 27-year-old vulnerability in OpenBSD, an operating system known for its security features, primarily used for running firewalls and critical infrastructure. This flaw enabled an attacker to remotely crash any computer running the OS merely by connecting to it.
- A 16-year-old vulnerability in FFmpeg was discovered, specifically within a line of code that automated testing tools had encountered five million times without detection. FFmpeg is widely utilized in software for video encoding and decoding.
- The model also independently identified and linked several vulnerabilities in the Linux kernel—the foundational software for the majority of global servers—facilitating an attacker’s escalation from standard user access to full machine control.
These vulnerabilities have been reported to their respective software maintainers, and all have been patched. Today, we are also providing a cryptographic hash of details for various other vulnerabilities (detailed on the Red Team blog), with the intention to disclose full specifics once fixes are implemented.
Evaluation benchmarks, such as CyberGym, underscore the significant advancements of Mythos Preview in comparison to our next best model, Claude Opus 4.6:
Cybersecurity Vulnerability Reproduction
In addition to our own findings, many partners have recently employed Claude Mythos Preview, generating a wealth of insights:
The robust cyber capabilities of Claude Mythos Preview stem from its exceptional coding and reasoning abilities. As illustrated in the evaluation results below, the model excels in various software coding tasks, achieving the highest scores among all developed models.
For further insights about the model’s capabilities, safety properties, and attributes, please refer to the Claude Mythos Preview system card.
While we currently have no plans to make Claude Mythos Preview broadly available, our ultimate objective is to facilitate secure deployment of Mythos-class models at scale—both for cybersecurity purposes and the diverse benefits these advanced models can offer. Achieving this requires ongoing development of cybersecurity safeguards to identify and mitigate the model’s most hazardous outputs. We anticipate launching new safeguards soon alongside the upcoming Claude Opus model, enabling us to enhance and refine them with a model that poses less risk than Mythos Preview3.
Plans for Project Glasswing
Today marks the inception of a long-term initiative. Its success hinges on widespread collaboration across the technology sector and beyond.
Project Glasswing partners will gain access to Claude Mythos Preview to discover and address vulnerabilities or weaknesses within their foundational systems—representing a significant portion of the global cyberattack surface. We expect this endeavor to focus on tasks such as local vulnerability detection, black box testing of binaries, endpoint security, and system penetration testing.
Anthropic’s commitment of $100 million in model usage credits to Project Glasswing and additional collaborators will cover substantial usage during this research preview. Subsequently, Claude Mythos Preview will be accessible to participants at a rate of $25/$125 per million input/output tokens (available via the Claude API, Amazon Bedrock, Google Cloud’s Vertex AI, and Microsoft Foundry).
Alongside our commitment to model usage credits, we have contributed $2.5 million to Alpha-Omega and OpenSSF through the Linux Foundation, and $1.5 million to the Apache Software Foundation to support open-source software maintainers in navigating this evolving landscape (maintainers interested in access can apply through the Claude for Open Source program).
We envision this effort expanding in scope and sustaining for many months, sharing valuable insights to help other organizations adapt their security practices. Partners will exchange information and best practices collaboratively; within 90 days, Anthropic will provide a public report detailing what we’ve learned, including vulnerabilities addressed and improvements achieved that can be disclosed. We will also work alongside leading security organizations to produce a set of practical recommendations for evolving security practices in the AI era. This may encompass:
- Vulnerability disclosure processes;
- Software update processes;
- Open-source and supply-chain security;
- Software development lifecycle and secure-by-design practices;
- Standards for regulated industries;
- Triage scaling and automation;
- Patching automation.
Anthropic has engaged in ongoing discussions with U.S. government officials regarding Claude Mythos Preview and its cyber capabilities—both offensive and defensive. As previously mentioned, securing critical infrastructure is a paramount national security priority for democratic nations; the advent of these cyber capabilities underscores the necessity for the U.S. and its allies to maintain leadership in AI technology. Governments play a crucial role in sustaining that advantage and in evaluating and mitigating the national security risks associated with AI models. We are prepared to collaborate with local, state, and federal representatives to assist in these initiatives.
Our hope is that Project Glasswing can catalyze a larger industry and public sector effort, with all stakeholders working to tackle significant questions regarding the implications of powerful AI models on security matters. We invite other members of the AI community to join us in establishing industry standards. In the medium term, the creation of an independent, third-party organization—uniting private and public-sector entities—could serve as an ideal foundation for continued large-scale cybersecurity projects.