How should I secure externally shared and private apps built with AI assistance?

The external applications should be completely separate from the internal network. Put them in an isolated hosting environment or DMZ with tightly restricted outbound and inbound access. Don’t let an internet-facing app talk directly to internal services unless there’s a specific, necessary path protected by authentication and least-privilege permissions. Zero-trust access controls can help for private apps, while a WAF, centralized logging, monitoring, vulnerability scanning, and endpoint detection can add layers around public ones.

Look closely at the software supply chain. Inventory every framework, package, runtime, and service, then track updates and known vulnerabilities. Ask who maintains the application, how security issues are reported, who responds when it breaks, and how ongoing development is funded. If there’s no clear owner or maintenance plan, keep it private or replace it. For public exposure, a managed cloud platform can reduce infrastructure risk, but it doesn’t eliminate application-level vulnerabilities.

Treat these like any other untrusted or early-stage applications. Before exposing one to the internet, understand its code, authentication, dependencies, data flows, update process, and logging. If you can’t explain its attack surface, it isn’t ready for external users. Keep it away from sensitive systems, use strong backups, and test it in a non-production environment first.