Ripple Introduces Comprehensive AI-Driven Security to XRPL: Over 10 Vulnerabilities Discovered, Next Release to Focus on Security Fixes

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

According to the disclosure, Ripple has established an AI-assisted "red team" to simulate attack behavior through fuzzing and automated adversarial testing, has currently discovered over 10 vulnerabilities, and is in the process of prioritizing fixes. The company stated that this move will shift the security mechanism from "passive fixing" to "active discovery."

On the development front, Ripple plans to modernize the XRPL code structure and enhance protocol change standards, requiring key updates to undergo multiple independent security audits and expanding the scope of bug bounties and community collaboration.

It is worth noting that the next version of XRPL will not introduce new features, focusing entirely on vulnerability fixes and system hardening, highlighting a significant increase in security priority. This measure comes as Ripple accelerates its expansion into institutional business, including stablecoin and real-world asset (RWA) use cases, placing higher demands on the underlying ledger security.