AI Security Institute Evaluates GPT‑5.5 and Claude Mythos for Vulnerability Detection
Test GPT‑5.5 and Claude Mythos on your codebase to compare vulnerability‑detection performance, and consider the cost‑effective lightweight model if prompt engineering is feasible.
Run the AI Security Institute's evaluation scripts against your code to benchmark GPT‑5.5 and Mythos, and document any differences in detection rates.
Summary
The AI Security Institute (ASI) recently evaluated OpenAI’s GPT‑5.5 for its ability to discover security vulnerabilities and found it performs on par with Anthropic’s Claude Mythos, a model that has already been benchmarked by the same institute. Both GPT‑5.5 and Mythos are generally available to developers, meaning they can be integrated into existing workflows without waiting for beta releases.
ASI also published a separate review of Mythos, detailing its strengths and limitations in a security context. In addition, a third article examines a smaller, cheaper model that can match the performance of GPT‑5.5 and Mythos when the prompt is carefully engineered. The analysis notes that while the lightweight model requires more scaffolding from the prompter, it delivers comparable results at a lower cost.
These findings suggest that teams can choose between GPT‑5.5, Mythos, or the cost‑effective alternative depending on budget and prompt‑engineering resources. The evaluations provide ready‑made benchmarks that can be used to validate vulnerability‑detection pipelines in production environments.
Key changes
- GPT‑5.5 is generally available and matches Claude Mythos in vulnerability detection
- ASI benchmark shows comparable performance between GPT‑5.5 and Mythos
- A separate ASI review details Mythos strengths and limitations
- A lightweight model can match GPT‑5.5/Mythos when prompts are carefully engineered
- The lightweight model requires more scaffolding but offers lower cost