AI-generated code introduces 15 vulnerabilities on average per codebase, but the actual risk depends on framework pairing more than the model used.
July 21, 2026
There may not be a clear winner in terms of which AI model is the best or worst for coding, but there are better (and far worse) models for organizations depending on the development environment or framework one codes in.
Software governance firm Secure Code Warrior today unveiled its AI Trust Index, a body of data attempting to quantify the risk established via large language model (LLM)-powered coding tools. AI-assisted development has become exceedingly popular at the organizational level, using tools to generate code, test for vulnerabilities, and audit for general integrity. It is by no means a secret that these tools are expensive, while introducing both vulnerabilities and risk, no matter the efficiency gains.
While this does not mean organizations should stay away from AI coding tools, it does mean one should be aware of the risks and mitigations before jumping into the deep end.
