Is AI-generated code a security risk?
It can be, in the same ways as code copied from the internet, only faster and in larger amounts. Coding assistants produce code that looks plausible and usually works, but may contain known vulnerability patterns such as injection flaws, weak cryptography or missing input checks; may call packages that do not exist, which attackers then register under that name with malicious content; may reproduce code under a licence your product cannot accept; and may embed secrets from examples. The tools themselves also send source code to the provider as context, so the choice of service and account matters for confidentiality. Treat AI output like a junior colleague's pull request: the same code review, automated security tests, dependency and licence scanning, and secret detection in the pipeline, with the developer remaining responsible. Decide which repositories may be shared with which assistant. From the Pro plan, NetSenX shows which developer machines and build servers send data to which AI services and how much; it cannot judge the quality of the code.