Table of Contents
Introduction
As a frequent user of ChatGPT, especially when connected through a U.S. VPN endpoint, I have sometimes run into the frustrating error: “Unable to load site.” Other times, the service may suggest turning off the VPN entirely. For users who rely on a VPN for privacy, routing, or regional network access, that advice is not always practical.
To make the setup easier to manage, I wrote a small Python script and shared it in my GitHub repository, The Art of Lazying. The script helps identify domains and IP addresses associated with ChatGPT-related traffic, so that VPN routing rules can be configured more deliberately instead of by guesswork.
The VPN Challenge
VPNs change the path your traffic takes across the internet. That is the point of using one, but it can also create problems for services that apply strict anti-abuse, regional, or risk-based access checks. When a service sees traffic coming from a shared VPN exit node, it may block the request, challenge it, or fail to load correctly.
For ChatGPT users, the visible symptom can be a page that refuses to load, repeated connection failures, or a message asking the user to disable the VPN. The practical challenge is not simply “VPN on” versus “VPN off.” A better approach is to understand which domains are involved and decide how that traffic should be routed.
My Python Script to the Rescue
The script is available here:
Its purpose is straightforward: collect a list of ChatGPT-related domains and resolve them to their corresponding IP addresses. With that information, a user can build more precise VPN rules, proxy rules, firewall rules, or split-tunnel configurations.
The workflow is:
- Maintain a list of domains used by ChatGPT and related services.
- Resolve each domain to one or more IP addresses.
- Print or export the mapping for use in local network configuration.
- Use the result to decide which traffic should go through the VPN and which traffic should bypass it.
Because cloud services change infrastructure over time, the exact IP addresses should be treated as temporary observations rather than permanent facts. Re-run the script when troubleshooting, after changing networks, or before updating routing rules.
Script in Action
When executed, the script fetches or resolves domains such as amp-api-edge.apps.apple.com, api.revenuecat.com, ios.chat.openai.com, and other related endpoints, then maps them to their current IP addresses.
That mapping can help answer practical questions such as:
- Which domains are involved when ChatGPT loads on this device?
- Which IP addresses are those domains resolving to right now?
- Which entries should be included in a VPN bypass list or split-tunnel rule?
- Has the service changed enough that my old routing rules are stale?
A typical usage pattern is to run the script locally, inspect the output, and then apply the resulting domains or IP ranges to the VPN client’s routing configuration. Different VPN clients handle this differently: some support domain-based rules, some support IP-based split tunneling, and some only support application-level routing.
The Advantage: More Reliable ChatGPT Access
With a more explicit view of ChatGPT-related traffic, VPN users can reduce the trial-and-error involved in fixing loading errors. Instead of disabling the VPN globally, they can make a narrower routing decision for the relevant traffic.
This approach keeps the benefits of VPN use where they are needed while making ChatGPT access more reliable. It is especially useful for users who frequently switch networks, use mobile devices, or maintain custom proxy/VPN configurations.
Conclusion
This Python script bridges the gap between secure VPN usage and uninterrupted ChatGPT access. By identifying the domains and IP addresses involved, it gives users a practical starting point for split tunneling and traffic management.
It also fits the spirit of The Art of Lazying: simplify a recurring technical annoyance, automate the tedious part, and leave behind a small tool that can be reused when the network changes.