108 karma · joined November 21, 2025
Client-Side: The -R 80:localhost:8080 Explained The 80 in -R 80:localhost:8080 is not a real port on the server. It's a virtual bind port that tells the SSH client what port to "pretend" it's listening on.
No port conflicts - The server doesn't actually bind to port 80 per tunnel. Each tunnel gets an internal listener on 127.0.0.1:random (ephemeral port). The 80 is just metadata passed in the SSH forwarded-tcpip channel. All public traffic comes through single port 443 (HTTPS), routed by subdomain.
So What Ports Are "Available" to Users?
Any port - because it doesn't matter! Users can specify any port in -R: ssh -t -R 80:localhost:3000 proxy.tunnl.gg # Works ssh -t -R 8080:localhost:3000 proxy.tunnl.gg # Also works ssh -t -R 3000:localhost:3000 proxy.tunnl.gg # Also works ssh -t -R 1:localhost:3000 proxy.tunnl.gg # Even this works!
The number is just passed to the SSH client so it knows which forwarded-tcpip requests to accept. The actual routing is done by subdomain, not port.
Why Use 80 Convention?
It's just convention - many SSH clients expect port 80 for HTTP forwarding. But functionally, any number works because:
- Server extracts BindPort from the SSH request - Stores it in the tunnel struct - Sends it back in forwarded-tcpip channel payload - Client matches on this to forward to correct local port - The "magic" is that all 1000 possible tunnels share the same public ports (22, 80, 443) and are differentiated by subdomain.
What it does:
- Expose localhost to the internet (HTTP/TCP/WebSockets) - Zero signup – just works immediately - Free
Nothing groundbreaking, just scratching my own itch for a no-friction tunnel service. Written in Go.
Link: https://tunnl.gg
Happy to answer questions or hear how you'd improve it.
Super Prompts is a decentralized knowledge repository designed to aggregate, validate, and distribute high-performance instructions for Artificial Intelligence agents. The system acts as a bridge between human intent and machine execution.
By standardizing prompt engineering techniques, we reduce token wastage and increase output fidelity across all major neural network architectures including GPT-4, Claude etc.