UK AISI Report: GPT-5.5 Cybersecurity Capabilities on Par with Claude Mythos
UK AISI finds GPT-5.5 matches Claude Mythos in cybersecurity, but GPT-5.5 is already public.
The UK AI Safety Institute (AISI) released its evaluation of OpenAI's GPT-5.5, finding its vulnerability discovery capabilities on par with Anthropic's Claude Mythos. The key difference is that GPT-5.5 is already publicly available, raising both defensive potential and misuse concerns. The report highlights the rapid convergence of frontier AI capabilities and the growing need for standardized safety evaluations across the industry.
Overview
The UK's AI Safety Institute (AISI) recently released its evaluation report on OpenAI's latest model, GPT-5.5, focusing on its cybersecurity capabilities. The institute had previously completed similar testing on Anthropic's Claude Mythos. The results show that GPT-5.5's performance in discovering security vulnerabilities is roughly on par with Claude Mythos — but with one key difference: GPT-5.5 is already publicly available.
Why AI Model Cybersecurity Capabilities Matter
The capabilities of large language models are advancing rapidly, amplifying both their potential and risks in the cybersecurity domain. AI models can help security researchers find and patch vulnerabilities faster, but they can also be exploited by malicious actors to identify system weaknesses and lower the barrier to launching attacks.
The UK AI Safety Institute is the world's first national-level AI safety evaluation body and has long conducted systematic testing of frontier AI models' cybersecurity capabilities. These evaluations help the public understand the true boundaries of AI capabilities and provide policymakers with critical decision-making references.
GPT-5.5 vs. Claude Mythos: Evaluation Results Compared
Vulnerability Discovery Capabilities at the Same Level
AISI's test results indicate that GPT-5.5's ability to discover security vulnerabilities is on par with Anthropic's Claude Mythos. The frontier models from both OpenAI and Anthropic have reached similar technical heights in this critical cybersecurity domain.
The Biggest Difference Lies in Public Availability
The most notable distinction between the two is availability. GPT-5.5 has already been released as a general-purpose product to the public, while Claude Mythos was still in a preview phase when it underwent evaluation. The real-world implications of this difference should not be overlooked: a widely available model means its cybersecurity capabilities are already having an impact in real-world environments — whether through positive security hardening or potential misuse.
Deeper Implications of the Evaluation Results
A Double-Edged Sword for the Cybersecurity Industry
AI models with vulnerability discovery capabilities represent a double-edged sword for the entire cybersecurity industry:
- Enhanced defense: Security teams can leverage these models to accelerate vulnerability scanning and code auditing, significantly reducing response times
- Lowered attack barriers: The same capabilities could also enable individuals without deep security expertise to discover and exploit vulnerabilities, expanding the potential threat surface
AI Safety Evaluation Moving Toward Standardization
AISI's approach of evaluating multiple frontier models using a unified framework is driving the standardization of AI safety assessments. By comparing different models' capabilities against the same test benchmarks, researchers and the public can gain more objective insights — which is crucial for establishing industry baselines and regulatory frameworks.
Rapid Convergence of Frontier Model Capabilities
The closeness of GPT-5.5 and Claude Mythos in cybersecurity capabilities reflects a broader industry trend: the capability gap between frontier AI models is narrowing. Major AI labs are rapidly catching up to each other across key capability dimensions. This not only intensifies commercial competition but also means that security risk assessments need to cover the entire industry rather than focusing on any single model.
Looking Ahead
As AI models' cybersecurity capabilities continue to improve, finding the balance between promoting security research applications and preventing malicious exploitation will be a core challenge for both the industry and regulators. The UK AISI's ongoing evaluation work brings much-needed transparency to this space and provides a replicable model for other countries looking to establish similar assessment mechanisms.
It's foreseeable that more countries and institutions will join the effort to evaluate AI cybersecurity capabilities, and AI developers will need to place greater emphasis on security capability assessments and risk mitigation measures before model releases.
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