San Francisco, USA — May 13, 2026 — OpenAI’s latest model, GPT-5.5, has achieved performance levels comparable to Anthropic’s Claude Mythos in cybersecurity vulnerability detection, according to recent evaluations by the UK’s AI Security Institute (AISI). This development marks the second major AI model to demonstrate advanced capabilities in completing complex cybersecurity tasks end-to-end, suggesting a broader trend in AI-driven security research rather than a single breakthrough.
The findings come as cybersecurity professionals and researchers grapple with the implications of increasingly sophisticated AI tools that can autonomously identify and exploit vulnerabilities—a capability that could reshape both offensive and defensive cybersecurity strategies. While GPT-5.5 may require more structured prompting to achieve similar results as Claude Mythos, its performance indicates that smaller, more accessible models can now match the capabilities of their more expensive counterparts.
This represents not the first time such a comparison has been made. In April 2026, AISI’s evaluation of Anthropic’s Claude Mythos Preview found it capable of completing a multi-step corporate network attack simulation—a task estimated to take a human cybersecurity expert around 20 hours. The new evaluation of GPT-5.5 suggests that OpenAI’s model has reached a similar level of proficiency in cybersecurity tasks, including vulnerability research, exploitation, and cryptography.
Note: This article includes verified details from the UK’s AI Security Institute’s evaluations. For technical specifics, see the institute’s published reports.
How AISI Evaluates AI Cyber Capabilities
The UK’s AI Security Institute employs a rigorous testing framework to assess AI models’ cybersecurity capabilities. Their evaluation suite includes 95 specialized tasks across four difficulty tiers, designed to test a wide range of skills:
- Basic tasks: Simple challenges like recovering flags from packet captures, cryptanalysis of misused ciphers, or reverse-engineering small binaries to locate hardcoded secrets. Models have fully mastered these tasks since at least February 2026.
- Advanced tasks: More complex simulations developed in collaboration with cybersecurity firms like Crystal Peak Security and Irregular. These focus on vulnerability research and exploitation against realistic targets with modern security mitigations, requiring significantly more steps and a larger search space.
GPT-5.5’s performance on these advanced tasks—particularly in vulnerability research and exploitation—indicates that OpenAI’s model can now operate at the frontier of AI-driven cybersecurity capabilities. This is notable because it suggests that smaller, more accessible models can achieve results previously only seen in larger, more expensive systems.
What This Means for Cybersecurity
The implications of GPT-5.5’s capabilities are significant for both offensive and defensive cybersecurity. On the offensive side, the ability of AI models to autonomously identify and exploit vulnerabilities could accelerate the pace of cyberattacks, making it easier for even less skilled actors to launch sophisticated campaigns. On the defensive side, organizations may need to invest in AI-driven security tools to keep pace with these evolving threats.
“This isn’t just about one model outperforming another,” says AISI’s evaluation team. “It’s about recognizing that AI models are now reaching a point where they can autonomously complete complex cybersecurity tasks that would have required human expertise just a few years ago.”
For cybersecurity professionals, this means a shift in how they approach threat detection and response. AI models like GPT-5.5 and Claude Mythos are not just tools for red-team exercises or penetration testing—they represent a new class of autonomous agents that can operate with minimal human intervention.
Comparing GPT-5.5 and Claude Mythos
While both models demonstrate advanced cybersecurity capabilities, You’ll see key differences in how they perform:
- Claude Mythos: Completed AISI’s corporate network attack simulation end-to-end, demonstrating a high level of autonomy in complex, multi-step tasks.
- GPT-5.5: Matches Mythos in performance but may require more structured prompting or scaffolding from users to achieve similar results. This suggests that while its capabilities are comparable, it may not yet operate with the same level of independence.
Despite these differences, the fact that two models from different developers—Anthropic and OpenAI—have achieved similar levels of performance is a clear indicator of a broader trend in AI development. “This is the first time we’ve seen two independent models reach this level of capability,” notes a cybersecurity expert familiar with AISI’s evaluations. “It’s a sign that the field is maturing rapidly.”
Who Benefits—and Who Might Be at Risk?
The rise of AI-driven cybersecurity tools has implications for multiple stakeholders:
- Cybersecurity firms: May need to adapt their tools and strategies to counter AI-driven threats, potentially leading to a new arms race in AI security.
- Enterprises: Could benefit from AI-powered threat detection but must also prepare for more sophisticated attacks.
- Governments and regulators: May need to update policies and frameworks to address the risks posed by AI-driven cyber capabilities.
- Individual users: While less directly impacted, the broader cybersecurity landscape could lead to more frequent and sophisticated phishing attacks or data breaches.
For now, the focus remains on how organizations can leverage these AI tools responsibly. “The key is not just to fear these capabilities but to understand how they can be used ethically and effectively,” says a spokesperson for Crystal Peak Security, one of the firms collaborating with AISI on these evaluations.
What Happens Next?
The next steps in this evolving landscape will likely include:
- Further refinements to AI models like GPT-5.5 and Claude Mythos to improve their autonomy and effectiveness in cybersecurity tasks.
- Development of countermeasures by cybersecurity firms to defend against AI-driven attacks.
- Potential regulatory discussions around the ethical use and governance of AI in cybersecurity.
For now, the focus remains on monitoring these developments closely. The UK’s AI Security Institute has not yet announced a specific timeline for further evaluations, but industry observers expect updates as models continue to evolve.
Key Takeaways
- GPT-5.5 now matches Claude Mythos in cybersecurity vulnerability detection, according to the UK’s AI Security Institute.
- Both models demonstrate advanced capabilities in vulnerability research, exploitation, and cryptography, suggesting a broader trend in AI-driven cybersecurity.
- GPT-5.5 may require more structured prompting but achieves comparable results, indicating that smaller models can now compete with larger, more expensive systems.
- The implications for cybersecurity are significant, with potential impacts on offensive and defensive strategies across industries.
- Stakeholders—including cybersecurity firms, enterprises, governments, and regulators—must adapt to these evolving capabilities.
As AI models continue to advance, the cybersecurity landscape will likely see further shifts. For now, organizations and individuals should stay informed about these developments and prepare for the potential risks and opportunities they present.
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