Research
Choose Wisely: AI-Generated Coding Risk Varies, A Lot
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Why it matters
AI-assisted coding tools are widely adopted at the organizational level, and this measurement of how framework choice drives vulnerability rates in generated code helps defenders quantify and mitigate the security debt introduced by LLM-powered development.
Secure Code Warrior, in collaboration with RMIT University, released its AI Trust Index, a study evaluating 1,760 complete codebases generated by 16 frontier LLMs from vendors including OpenAI, Anthropic, and Google. The research found AI-generated code introduces roughly 15 vulnerabilities per codebase on average, with actual risk depending more on the development framework pairing than on the model chosen.