Study Finds Widespread Security Vulnerabilities in AI-Generated Automation Code Across Major Models
A new arXiv preprint reports that code generated by ChatGPT, Microsoft Copilot, and Google Gemini for routine automation tasks consistently contained exploitable security vulnerabilities. The study found that 9 out of 17 vulnerability classes appeared in code from all three models, and overall risk scores were similar across platforms, suggesting the vulnerabilities are linked to the nature of the tasks rather than any specific model.
Why it matters: This highlights a broad security risk in deploying LLM-generated automation code without human review, regardless of the AI tool used.
Full story at: arXiv Cryptography and Security ↗