Ripple introduces AI to comprehensively strengthen XRPL: Over 10 vulnerabilities have been discovered, the next version will focus on security fixes.

BlockBeats message, March 28, Ripple Labs announced that it will introduce an AI-driven security framework into the XRP Ledger, using machine learning tools throughout the entire process of code review, adversarial testing, and vulnerability discovery to address the security challenges brought by the growth of institutional applications.

According to disclosures, Ripple has assembled an AI-assisted “red team.” Through fuzz testing (fuzzing) and automated adversarial testing that simulates attack behavior, it has already identified more than 10 vulnerabilities and is prioritizing their remediation. The company said this move will shift security mechanisms from “passive patching” to “active discovery.”

On the development side, Ripple plans to modernize the XRPL code structure, while also raising protocol change standards. It will require that critical updates go through multiple independent security audits, and it will expand the scope of bug bounties and community collaboration.

It’s worth noting that the next version of XRPL will not introduce new features, and will be entirely focused on vulnerability fixes and system hardening, highlighting a significant increase in security priority. The initiative comes as Ripple accelerates its expansion into institutional business, including stablecoin and real-world asset (RWA) application scenarios, which place higher demands on the security of the underlying ledger.