Ripple announced the integration of artificial intelligence to bolster the security of the XRP Ledger (XRPL) as part of preparations for the network’s next phase of scaling.
Transition to Proactive Security
The company stated a shift from a reactive security model to a proactive approach, where vulnerabilities are identified before they reach production.
The new strategy involves using AI at all stages of development—from testing to threat analysis and code change verification.
Security is viewed not as a one-time audit but as a continuous process that must scale with the network’s growth.
What Will Change
The updated security model includes:
- AI-driven code testing and analysis;
- establishing a specialized “red team” to simulate attacks;
- tightening requirements for protocol updates and changes;
- deeper threat modeling and exploitation scenario analysis.
According to the company, AI tools have already helped identify several vulnerabilities in the early stages of development.
Responding to Network Growth and Complexity
Ripple linked the updated approach to the expanded use of XRPL. The network is employed for global payments, asset tokenization, and institutional solutions, increasing reliability demands.
The company stated that the blockchain, launched in 2012, has processed over 100 million ledger entries and more than 3 billion transactions, facilitating significant fund transfers.
Ripple emphasized that further infrastructure development (including work with tokenized assets and institutional clients) requires a new level of resilience and security, with AI becoming a key architectural element. The advancement of technology heightens threats: malicious actors also begin using similar tools to find vulnerabilities, necessitating a symmetrical response from developers.
Earlier, during a two-week experiment, the AI model Claude Opus 4.6 from Anthropic identified 22 vulnerabilities in the Firefox browser. Fourteen issues were classified as highly severe.