* feat: native udpgw protocol alongside existing UDP associate Why udpgw is needed even with UDP associate: UDP associate (udp_open/udp_data) creates one tunnel session per UDP destination and polls each independently. On high-latency or shaky networks this compounds — N simultaneous UDP flows need N separate polling loops, each paying its own batch round-trip overhead. Google Meet calls, which fire dozens of concurrent STUN + RTP flows, stall or fail entirely because the per-destination polling can't keep up. udpgw multiplexes ALL UDP over one persistent TCP-like session using conn_id framing. One batch op carries frames for many destinations. Persistent sockets per (conn_id, dest) with continuous reader tasks keep source ports stable — critical for protocols like Telegram VoIP and STUN that expect replies on the same port. Both paths coexist — they serve different traffic: - UDP associate (SOCKS5): apps that negotiate SOCKS5 UDP relay - udpgw (198.18.0.1:7300): TUN-captured UDP (DNS, QUIC, Meet, etc.) tun2proxy vendored as git submodule at v0.7.20 with one transparent commit adding udpgw_server to the Android JNI run() function. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: block QUIC (UDP 443) and DNS (UDP 53) from udpgw QUIC through udpgw is slower than TCP/HTTP2 through the batch pipeline — blocking it forces browsers to fall back to TCP, improving YouTube and general browsing speed. DNS is better handled by tun2proxy's virtual DNS / SOCKS5 UDP associate path which is more reliable for single request-response exchanges. VoIP (Telegram, Meet) still flows through udpgw normally. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: replace submodule with [patch.crates-io] for tun2proxy udpgw Use the idiomatic Rust [patch.crates-io] mechanism instead of a git submodule. Points to yyoyoian-pixel/tun2proxy fork with the udpgw JNI parameter patch (upstream PR: tun2proxy/tun2proxy#247). Will be removed once upstream ships the change in tun2proxy >= 0.8. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * chore: pin tun2proxy patch SHA in Cargo.lock Locks tun2proxy at dfc24ed1 so the patch resolution is recorded and any branch rewrite is visible in the lockfile diff. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: use AbortHandle for ConnSocket readers to prevent FD leaks JoinHandle::drop detaches the task without aborting it. When udpgw_server_task is cancelled (session close), the post-loop cleanup never runs and per-(conn_id, dest) reader tasks become zombies holding Arc<UdpSocket> file descriptors. AbortHandle::drop aborts the task automatically, so cleanup is correct by construction regardless of how the parent task exits. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: yyoyoian-pixel <279225925+yyoyoian-pixel@users.noreply.github.com> Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Tunnel Node
HTTP tunnel bridge server for MasterHttpRelayVPN "full" mode. Bridges HTTP tunnel requests (from Apps Script) to real TCP connections.
Architecture
Phone → mhrv-rs → [domain-fronted TLS] → Apps Script → [HTTP] → Tunnel Node → [real TCP] → Internet
The tunnel node manages persistent TCP and UDP sessions. TCP sessions are real TCP connections to a destination server; UDP sessions are connected UDP sockets to one destination host:port. Data flows through a JSON protocol:
- connect — open TCP to host:port, return session ID
- data — write client data, return server response
- udp_open — open UDP to host:port, optionally send the first datagram
- udp_data — send one UDP datagram, or poll for returned datagrams when
dis omitted - close — tear down session
- batch — process multiple ops in one HTTP request (reduces round trips)
Deployment
Cloud Run
cd tunnel-node
gcloud run deploy tunnel-node \
--source . \
--region us-central1 \
--allow-unauthenticated \
--set-env-vars TUNNEL_AUTH_KEY=$(openssl rand -hex 24) \
--memory 256Mi \
--cpu 1 \
--max-instances 1
Docker — prebuilt image (any VPS)
The fastest path. Pull a prebuilt image and run it; no Rust toolchain needed on the VPS.
# Generate a strong secret. Save it — you'll paste the same value into CodeFull.gs.
SECRET=$(openssl rand -hex 24)
echo "Your TUNNEL_AUTH_KEY: $SECRET"
# Pull + run.
docker run -d \
--name mhrv-tunnel \
--restart unless-stopped \
-p 8080:8080 \
-e TUNNEL_AUTH_KEY="$SECRET" \
ghcr.io/therealaleph/mhrv-tunnel-node:latest
The :latest tag tracks the most recent release. To pin a specific version (recommended for production), use ghcr.io/therealaleph/mhrv-tunnel-node:v1.5.0 (or whatever release you're on). Image is available for linux/amd64 and linux/arm64.
docker-compose.yml if you prefer:
services:
tunnel:
image: ghcr.io/therealaleph/mhrv-tunnel-node:latest
restart: unless-stopped
ports:
- "8080:8080"
environment:
TUNNEL_AUTH_KEY: ${TUNNEL_AUTH_KEY}
Then TUNNEL_AUTH_KEY=your-secret docker compose up -d.
Docker — build from source
If you'd rather build the image yourself (or add custom changes):
cd tunnel-node
docker build -t tunnel-node .
docker run -p 8080:8080 -e TUNNEL_AUTH_KEY=your-secret tunnel-node
Direct binary
cd tunnel-node
cargo build --release
TUNNEL_AUTH_KEY=your-secret PORT=8080 ./target/release/tunnel-node
Environment Variables
| Variable | Required | Default | Description |
|---|---|---|---|
TUNNEL_AUTH_KEY |
Yes | changeme |
Shared secret — must match TUNNEL_AUTH_KEY in CodeFull.gs |
PORT |
No | 8080 |
Listen port (Cloud Run sets this automatically) |
Protocol
Single op: POST /tunnel
{"k":"auth","op":"connect","host":"example.com","port":443}
{"k":"auth","op":"data","sid":"uuid","data":"base64"}
{"k":"auth","op":"close","sid":"uuid"}
Batch: POST /tunnel/batch
{
"k": "auth",
"ops": [
{"op":"data","sid":"uuid1","d":"base64"},
{"op":"udp_data","sid":"uuid2","d":"base64"},
{"op":"close","sid":"uuid3"}
]
}
→ {"r": [{...}, {...}, {...}]}
Health check: GET /health → ok
Performance: deployment count and pipeline depth
The mhrv-rs client runs a pipelined batch multiplexer in full mode. Each Apps Script round-trip takes ~2s, so the client fires multiple batch requests concurrently — the pipeline depth equals the number of configured script deployment IDs (minimum 2, no upper cap).
More deployments = more concurrent batches hitting the tunnel-node = lower per-session latency. With 6 deployments, a new batch arrives every ~0.3s instead of every 2s.
The tunnel-node itself is stateless per-request (sessions are keyed by UUID), so it handles concurrent batches naturally. For best results, deploy 3–12 Apps Script instances across separate Google accounts and list all their deployment IDs in the client config.