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Blockchain News

XRP Ledger Averts $80B Critical Hack as AI Uncovers Major Flaw

Ripple has outlined a roadmap to enhance XRPL security, which includes adding AI-assisted code audit pipelines.

Written By:
Dhara Chavda

Reviewed By:
Divya Mistry

Last updated: February 27, 2026 2:59 PM
Published February 27, 2026 2:23 PM
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Last updated: February 27, 2026 2:59 PM
Published February 27, 2026 2:23 PM
AI Saves XRPL from Potential $80 Billion Exploit

Key Highlights

  • A major logic flaw was discovered in the signature-validation logic of a proposed XRP Ledger (XRPL) amendment.
  • The vulnerability was identified by a security engineer and an autonomous AI security bot from cybersecurity firm Cantina.
  • The XRPL Foundation immediately issued an emergency release (rippled 3.1.1) to block the amendment from activating on the mainnet.

A potential catastrophe for the XRP ecosystem was narrowly avoided after a swift identification and patching of a critical security vulnerability. This vulnerability, which could have put an estimated $80 billion in assets at risk, was discovered in a proposed amendment to the XRP Ledger (XRPL) before it could be activated.

The flaw, identified as a “critical logic flaw” in the signature-validation logic of the XRPL Batch amendment, was uncovered on February 19, 2026, by Pranamya Keshkamat, a security engineer at Cantina, and Cantina’s AI security bot, Apex. The Batch amendment, at the time, was in its voting phase among XRPL validators and had not yet been activated on the mainnet.

A critical logic flaw

The vulnerability centered on the signature validation code within the amendment. If exploited, an attacker could have executed unauthorized “inner transactions” on behalf of arbitrary victim accounts. These transactions could have ranged from unauthorized fund transfers to significant ledger state changes, all without the need for the victim’s private keys.

Specifically, the “root cause” of the vulnerability lay in the code responsible for validating signers of batch transactions. In the proposed amendment, inner transactions within a batch were intentionally unsigned, relying on the outer batch’s list of signers for authorization. The validation function contained a loop error: when it encountered a signer whose account did not yet exist on the ledger (a common scenario for new accounts), it would prematurely declare success and exit, skipping the validation of all other remaining signers.

This flawed logic created an exploit path. An attacker could construct a batch transaction including a new, attacker-controlled account, a simple transaction from that account (making it a required signer), and a payment from a victim account to the attacker. They would then provide two signer entries: one legitimate one for their new account, and a forged one for the victim account signed with their own key. Due to the loop error, the validation process would exit successfully after checking the first (legitimate) entry, failing to validate the second forged one and allowing the unauthorized transaction to proceed.

Swift action and mitigation

Upon discovery, the vulnerability was responsibly disclosed to Ripple’s engineering teams, who promptly validated the report. Recognizing the severity of the threat, the XRPL Foundation immediately advised Unique Node List (UNL) validators to vote against the activation of the Batch amendment.

According to a blog post, an emergency release of the XRPL software, rippled 3.1.1, was published on February 23, 2026. This release marked both the Batch amendment and a related amendment, fixBatchInnerSigs, as unsupported, effectively blocking them from being activated on the network. This immediate remediation ensured that the vulnerability could not be exploited.

Furthermore, a corrected replacement amendment, BatchV1_1, has been implemented and is currently undergoing thorough review before any future deployment. This revised version addresses the identified flaw, includes additional authorization guards, and tightens the scope of the signing check to prevent similar vulnerabilities.

Destabilization and trust loss

While no funds were ever at risk due to the vulnerability being patched prior to activation, the potential consequences of a successful exploit were severe. XRPLF stated that exploitation could have “destabilized the ecosystem,” leading to a “substantial loss of confidence in XRPL” and causing significant disruption to the broader blockchain landscape.

Hari Mulackal, CEO of Cantina and Spearbit, emphasized the scale of the potential risk, stating that had this vulnerability been exploited, it could have resulted in the “largest security hack by dollar value in the world,” with nearly $80 billion directly at risk, potentially referring to the total market capitalization of XRP at the time.

The rise of AI in cybersecurity

This incident also highlights the growing importance of AI in the field of cybersecurity. Cantina’s autonomous bug hunter, Apex, was instrumental in identifying the vulnerability through static analysis of the XRPL codebase. AI security tools are increasingly being deployed to augment human security efforts, particularly in identifying complex logic flaws that might be overlooked during manual reviews.

The trend towards AI-driven security is gaining traction, with companies like Anthropic recently releasing Claude Code Security, an AI cybersecurity vulnerability scanner. The increasing adoption of these tools suggests a shift towards proactive and automated security measures in the blockchain industry.

In response to this incident, Ripple has outlined a roadmap to enhance XRPL security, which includes adding AI-assisted code audit pipelines to the standard review process and extending static analysis coverage to flag potential vulnerabilities.

The swift action taken by the XRPL Foundation and the effective use of AI security tools in this instance demonstrate the importance of proactive security measures and collaborative efforts in protecting blockchain ecosystems. While the potential for major exploits remains, incidents like this show that with vigilance and the right tools, these threats can be identified and neutralized.

Also Read: Is XRP Centralized? Ripple CTO Slams Critics in Epic Twitter Debate

Disclaimer: The information researched and reported by The Crypto Times is for informational purposes only and is not a substitute for professional financial advice. Investing in crypto assets involves significant risk due to market volatility. Always Do Your Own Research (DYOR) and consult with a qualified Financial Advisor before making any investment decisions.

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TAGGED:Artificial Intelligence (AI)XRP Ledger
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Dhara Chavda- Crypto Research Analyst at The Crypto Times
By Dhara Chavda
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Dhara Chavda is a Content Strategist and Research Analyst with 5 years of experience in the crypto industry. She holds a Bachelor’s degree in Computer Engineering and brings a strong technical perspective to her work. Dhara specializes in DeFi, price analysis, and the core mechanics of cryptocurrencies. She also works on crypto news, including research, analysis, and assigning stories, ensuring accurate and timely coverage of key developments in the space.
Divya Mistry - Content Editor at The Crypto Times
By Divya Mistry
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Divya Mistry is a Content Editor with over 9 years of experience in news, PR, marketing, and research. Armed with a Master’s Degree in English Literature from the University of Mumbai, she specializes in crafting and refining long-form content across digital and print platforms. Over the years, Divya has contributed to and shaped content for leading brands across a range of industries, including real estate, healthcare, vertical transport, entertainment, lifestyle, education, EdTech, tech, and finance. Her research work has been featured on platforms like DNA India, Forbes, and Elevator World India. She now brings her editorial and research skills to explore the rapidly evolving world of cryptocurrency.

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