OpenAI Claims GPT-5.5 Cyber Beats Anthropic Mythos on Security Test
OpenAI says its new GPT-5.5 Cyber model outperformed Anthropic’s Mythos on a dedicated cybersecurity benchmark. The company released results showing GPT-5.5 Cyber scored higher in autonomous vulnerability discovery and exploitation tasks.
The benchmark, known as CyberSecEval, measures how well AI models can identify and patch security flaws. OpenAI claims GPT-5.5 Cyber achieved a 78% success rate compared to Mythos’s 62%.
The Lede: Who, What, When, Why
OpenAI published the findings in a blog post Wednesday. GPT-5.5 Cyber is a specialized version of the GPT-5.5 model fine-tuned for security research. Anthropic’s Mythos is a comparable safety-focused model designed for red-teaming and penetration testing.
The results matter because both companies are competing to lead in AI-driven cybersecurity. Enterprise customers increasingly demand models that can autonomously find and fix vulnerabilities without human oversight.
How the Benchmark Worked
The CyberSecEval test included 120 simulated attack scenarios. Each scenario required the AI to:
- Identify a software vulnerability in a realistic codebase.
- Exploit the flaw to gain unauthorized access.
- Suggest a remediation patch.
- Document the attack chain.
OpenAI stated that GPT-5.5 Cyber completed 78% of these tasks successfully. Mythos handled 62%. Both models were given identical time limits and tool access.
“This is a significant milestone in our ability to automate defensive cybersecurity,” an OpenAI spokesperson said in the release. “We believe these models can augment human security teams, not replace them.”
What Makes GPT-5.5 Cyber Different
The key improvement comes from retraining on curated security data. OpenAI used thousands of real-world vulnerability reports and patch histories. The model also received fine-tuning on adversarial thinking — how to step through an attacker’s decision process.
Anthropic’s Mythos, by contrast, was trained with a strong safety alignment that sometimes limits its ability to simulate aggressive attack behaviors. That constraint may have hurt its benchmark score.
Methodology and Limitations
OpenAI acknowledged the benchmark only covers a narrow slice of cybersecurity tasks. The test did not measure defensive capabilities like monitoring logs or triaging alerts. It also excluded physical or social engineering attacks.
Both models were evaluated in a sandboxed environment with no internet access. Real-world security work involves far more ambiguity and messy data.
Industry Reaction
Security researchers expressed caution. Dr. Alice Thornton, a cybersecurity professor at MIT, warned: “Benchmarks are useful but not predictive. A model that scores well in a lab may fail spectacularly in production.”
Others noted that OpenAI’s internal testing could be biased. The company has not released independent third-party validation.
Background: AI vs. AI in Security
The race to build specialized cybersecurity AI models intensified in 2024. Google, Microsoft, and Meta all launched similar initiatives. OpenAI’s GPT-5.5 Cyber and Anthropic’s Mythos represent the two most advanced public examples.
Both models are currently available only through enterprise APIs and require significant compute resources. Pricing has not been disclosed.
Bottom Line
OpenAI claims GPT-5.5 Cyber beats Anthropic’s Mythos on a cybersecurity benchmark. Independent verification is still missing. For now, the claim adds fuel to the ongoing competition between the two leading AI safety companies.
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