Developers are increasingly using AI to analyze code, detect bugs, and even identify security vulnerabilities. Tools powered by large language models promise faster development and automated security insights.
But during testing, we discovered something surprising.
When we analyzed the same code with three different AI models — OpenAI, Claude, and Gemini — the vulnerability reports often looked completely different.
Sometimes one model flagged a critical security issue while the other two did not detect anything. In other cases, two models agreed while the third suggested a completely different fix.
This inconsistency raises an important question:
