Which AI Model Codes Most Securely?

See how 16 leading AI models actually code, scored across 11 real-world frameworks and 1,760 codebases — the framework matters as much as the model.

You'll learn:

• Why even the top-ranked model still isn't safe by default — the highest scorer in the study produced 196 confirmed critical/high-severity vulnerabilities of its own
• Why price tells you almost nothing about security — the most expensive model costs 31× more than a top-5 competitor, and still isn't the safest choice
• Why framework context shapes model performance — one model ranks 5th overall, then finishes dead last the moment you change the framework
• How to correctly read a 0–100 Trust Index score — and why comparing scores across two different frameworks can be misleading if you don't know the method
• Which handful of CWE categories account for the majority of every confirmed vulnerability in the study — a concentrated, and therefore solvable, problem
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Methodology note: "The foundational study — 6 models, 660 codebases, 11 frameworks — was co-authored with RMIT University. Secure Code Warrior subsequently and independently extended that same methodology to 16 models and 1,760 codebases. Both phases used identical generation, scanning, verification, and scoring — the results are fully comparable."

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