Critical Vulnerabilities Identified in Bitcoin's Lightning Network

Developers have flagged a newly discovered vulnerability in Bitcoin's Lightning Network that they say could expose users to potential fund losses. Nodes running version 26.04 or later are considered at risk. As an immediate precaution, the team is urging operators to suspend routing and payment processing. For those who cannot fully shut down a node, the recommended alternative is to restart the background process with the \u0022offline\u0022 parameter. In offline mode, the node disconnects from other Lightning Network peers and cannot send, receive, or route payments, while continuing to run and track the Bitcoin blockchain. The issue has been assigned a CVE identifier, though technical details have not been disclosed. A two-week reporting embargo is intended to give operators time to deploy patches before attackers can study code changes. AI-assisted security analysis has surfaced Bitcoin-related issues before. In late July, a group calling itself Bitcoin Red Team—a 16-developer collective—said it used AI models to scan 390 Bitcoin project repositories and found nearly 5,000 security issues, including 85 labeled critical and 635 rated high severity. The group did not publish detailed vulnerability breakdowns. The Lightning Network is a layer built on top of the Bitcoin blockchain designed to enable faster, lower-cost transactions by keeping most payments off-chain. Participants lock bitcoin into a shared payment channel and update balances between them over time; only the final state is recorded on the blockchain when the channel is closed. To protect funds, a node must remain online and monitor the network so it can react on-chain if a counterparty attempts to close a channel using outdated data—something a fully powered-off machine cannot do. Separately, Ledger CTO Charles Guillemet previously said a vulnerability affecting clear signing in the Ethereum app had been patched. The issue was found by Ledger's Donjon team using an AI-powered vulnerability detection system.