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A critical vulnerability in the XRP Ledger was identified and patched in February 2026 before it could reach the live network, after an AI security tool developed by Cantina and cybersecurity engineer Pranamya Keshkamat detected a signature-validation flaw that its creators say could have put nearly $80 billion at risk.
The XRPL Foundation confirmed that no funds were lost because the affected feature was still in a pre-deployment voting phase and never activated on the mainnet.
According to the XRPL Foundation’s official disclosure report, the vulnerability existed within the signature-validation logic of a proposed network upgrade known as the “Batch” amendment.
The feature was designed to allow multiple transactions to be grouped into a single operation to improve efficiency and scalability.
However, a logic error created a dangerous loophole. Under certain conditions, the system could incorrectly validate transaction signatures.
“The amendment was in its voting phase and had not been activated on mainnet; no funds were at risk.” The XRPL Foundation said in a public statement.
Security researchers warned that exploitation could have allowed attackers to drain accounts, alter ledger states, or submit unauthorized account actions.
In a worst-case scenario, such an attack might have triggered widespread panic and loss of confidence across the XRP ecosystem.
The foundation noted that a successful exploit could have caused substantial loss of confidence in XRPL, with potentially significant disruption for the broader ecosystem.
The discovery marks a an important milestone for AI-assisted security auditing in blockchain development.
Cantina’s autonomous AI system, known as Apex, identified the flaw through automated static analysis of the XRPL codebase.
“Our autonomous bug hunter, Apex, found this critical bug. Had this been exploited, it would have been the largest security hack by dollar value in the world, with nearly $80 billion at direct risk.” Hari Mulackal, CEO of Cantina and Spearbit, said.
After detecting the issue, researchers submitted a responsible disclosure report, enabling Ripple and XRPL engineers to validate the vulnerability and begin emergency mitigation procedures the same day.
Validators were quickly advised to vote against activating the amendment, effectively preventing the flawed upgrade from going live.
An emergency software update rippled version 3.1.1 was released on Feb. 23 to block activation entirely while developers implemented a corrected replacement upgrade.
Industry observers say the incident demonstrates how AI is becoming an essential layer of defense as blockchain protocols grow more complex and financially significant.
The near-miss highlights an often overlooked reality: blockchain security risks do not only arise from external hackers but also from software upgrades intended to improve networks.
Unlike traditional financial systems, blockchain code operates transparently and often immutably once deployed, meaning bugs introduced during upgrades can carry systemic consequences if not detected early.
The XRPL incident shows how governance mechanisms, including validator voting and staged deployment can act as safeguards.
The discovery also reinforces a broader trend toward automated security auditing.
As decentralized networks expand, manual reviews alone may no longer be sufficient to identify subtle logic flaws embedded in millions of lines of code.
Security analysts increasingly view AI-driven tools as complementary to human researchers rather than replacements.
In this case, collaboration between a human engineer and AI scanning technology prevented a vulnerability that could have impacted billions of dollars in market value tied to XRP.
The XRPL Foundation publicly released a detailed vulnerability disclosure outlining the discovery timeline, technical cause, and remediation steps.
Validators coordinated quickly to block activation, engineers issued emergency patches within days, and a corrected amendment is now undergoing additional review before any future deployment.
Rather than exposing systemic weakness, analysts say the episode may ultimately reinforce trust in the XRP Ledger’s governance model by demonstrating that safeguards worked as designed.
As AI-powered cybersecurity tools become more common across crypto infrastructure, similar pre-deployment discoveries could increasingly prevent catastrophic exploits before users ever face risk.
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