XRPL Prepares Firewall Defense Against Rising Scam Threats

A loose but growing push is under way in the XRP community to build what some people call an “XRP firewall” — a set of tools and checks meant to block scams on the XRPL.

Vet, one of the dUNL validators on the XRP Ledger, has hinted at a big update that could change the fight against scams on XRPL.

The feature, known as the XLS-86 Firewall, is still in development but is being described as a possible endgame for fraudsters.

In a recent post, Vet said the amendment would act as a safeguard to stop losses of XRP, tokens, and NFTs when activated.

If approved and rolled out, it could give users a much stronger line of defense against common traps that have cost the community millions over the years.

Just recently a high-profile patch was published after developers found malicious packages related to the xrpl.js library on NPM, and that incident has sharpened urgency around better protections.

Tools And Reporting Systems

Several public resources already try to do the job of a firewall in pieces. According to XRPL.org, users can file scam reports and get guidance on suspicious activity.

Reports have disclosed that forensics platforms such as XRplorer keep databases of addresses linked to fraud and illicit transfers; those lists are used by wallets and exchanges to warn or block interactions.

The pieces exist, but they are spread across sites and teams, not bundled as one single shield for everyday users.

A Critical Software Warning

According to market watchers, the most recent shock came when developers discovered compromised or malicious versions of xrpl.js pushed to NPM, the package registry many apps use.

The issue was patched on April 23, 2025 after maintainers removed the bad releases and urged users to update.

How A Firewall Could Work

A practical firewall would combine several simple features. It could auto-flag addresses with histories of fraud. Wallets might show a clear warning before a user approves a payment to a flagged account.

Exchanges and node operators could share lists to reduce the chance that a scammer moves funds freely.

Machine learning could be used to spot repeat patterns of phishing messages or cloned domains, while human teams would still verify hard cases.

Featured image from Meta, chart from TradingView