Bitcoin Core developer Antoine Poinsot announced a revision to the project’s security disclosure policy, citing the increased ability of large language models (LLMs) to rapidly identify software vulnerabilities. In an email to the Bitcoin Development Mailing List on Thursday, Poinsot explained that traditional lengthy disclosure embargoes, previously used to protect users by delaying public details until upgrades were available, no longer offer sufficient protection against AI-assisted discovery. The secrecy required for these embargoes often prevented fixes from being backported to older versions, leaving users exposed until the next major release.

Under the new framework, vulnerabilities classified as "easily discoverable"—defined as flaws that can be found with minimal effort, such as through simple LLM prompts—will receive immediate fixes across all maintained major versions. Security advisories will be published concurrently with these updates. This shift aims to reduce the window of exposure for users who cannot immediately upgrade to the latest version. Other vulnerabilities will continue to follow severity-based disclosure schedules: low-severity issues will be disclosed two weeks after a fix is released in a major version, while medium and high-severity bugs will be revealed two weeks after the last affected release reaches its End of Life, typically one year post-fix. Critical bugs remain outside this standard policy, requiring ad-hoc procedures.

The update reflects growing pressure on Bitcoin’s software ecosystem from AI-driven security research. In August, the volunteer Bitcoin Red Team reported nearly 5,000 potential issues across 390 projects, though only about a fifth had been reproduced at that time. Similarly, Core Lightning developers recently urged operators to upgrade or take nodes offline after receiving multiple AI-generated vulnerability reports, withholding technical details for two weeks. Luke de Wolf, author of "Defending Bitcoin," endorsed the change despite past disagreements with Poinsot’s approach.