LN Gossip Visualizer

Seeing how information travels across the Lightning Network

The LN Gossip Visualizer is a tool for observing, analyzing, and visualizing how gossip messages propagate across the Lightning Network. It answers a deceptively simple question: when a node announces something to the network, how does that information spread?

Why This Matters

The Lightning Network relies on a gossip protocol for nodes to discover each other, learn about available channels, and compute payment routes. This protocol is defined in BOLT #7 and operates as a peer-to-peer flood-fill: when a node receives a new gossip message, it forwards it to all its other peers.

But how well does this actually work in practice? How fast does information reach the entire network? Are there bottlenecks? Can an observer figure out who originated a message by watching propagation patterns?

These are the questions the LN Gossip Visualizer helps explore.

Standing on Solid Foundations

The LN Gossip Visualizer is built on top of the gossip_observer project by Jonathan Harvey-Buschel (@jharveyb). Jonathan designed and implemented the core infrastructure that makes this work possible: the Rust-based gossip collector, the archiver pipeline, the data storage layer, and the deployment tooling. His work on passive gossip observation — connecting to hundreds of Lightning peers, recording message timing with nanosecond precision, and exporting structured datasets — is the cornerstone on which this visualizer is built.

Our contribution layers an interactive visualization dashboard on top of Jonathan’s data collection infrastructure, making the propagation patterns visible and explorable.

What You’ll Find in This Book

• Part 1 explains what LN gossip is and why studying it matters
• Part 2 describes the passive observer (built by @jharveyb) that connects to hundreds of peers and records every gossip message
• Part 3 walks through the interactive dashboard — propagation replay, geolocation map, fingerprinting, and leak detection
• Part 4 shares findings from the dataset
• Part 5 outlines future directions

You can explore the live prototype at prototype-ln-gossip.vercel.app.