Introduction
In a world where infrastructure security is critical, large language models (LLMs) offer new dimensions of analysis and protection. Recently, at Cloudflare, we had the opportunity to test Mythos Preview, an LLM from Anthropic, as part of our Project Glasswing. This model was applied to over fifty of our repositories to evaluate its ability to identify and exploit vulnerabilities. Here’s what we discovered.
A Significant Advancement with Mythos Preview
Mythos Preview marks a major leap forward compared to previous LLMs. Unlike general-purpose models, Mythos focuses on security analysis, delivering results comparable to the work of an experienced researcher rather than a mere automated scanner.
Exploit Chain Construction
One of the standout features of Mythos Preview is its ability to construct exploit chains. Real attacks do not simply exploit a single vulnerability; they chain multiple attack primitives to create a functional exploit. For instance, Mythos could transform a "use-after-free" bug into an arbitrary read and write primitive, thus hijacking the control flow and using return-oriented programming (ROP) chains to fully control a system.
Proof Generation
Finding a bug is one thing; proving it’s exploitable is another. Mythos Preview accomplishes both. It writes code to trigger the suspected bug, compiles it in a test environment, and runs it. If the program behaves as expected, that's proof. If not, the model adjusts its hypotheses and tries again, illustrating a continuous learning and adaptation process.
Implications for Infrastructure Security
The capabilities of Mythos Preview raise important questions about the evolution of infrastructure security. According to a recent Gartner study, the infrastructure security market is expected to reach $187 billion by 2025. With tools like Mythos, companies can anticipate complex attacks, thereby reducing the cost and impact of security incidents.
Towards Large-Scale Adoption
For models like Mythos Preview to be adopted at scale, adjustments are necessary. This includes optimizing the model's architecture and related processes to ensure seamless integration into existing security systems.
Conclusion
In sum, Mythos Preview offers a new and powerful perspective for infrastructure protection. By combining exploit chain construction and proof generation, it redefines what we can expect from LLMs in the security domain.
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