Malicious code in @xayz/baileys (npm)
The @xayz/baileys npm package, a fork of the Baileys WhatsApp Web library, contains malicious code that silently subscribes the victim's WhatsApp account to attacker-controlled channels without user consent. This is done by injecting a covert FOLLOW query into the WhatsApp socket connection using the installer's authenticated session. The target channels are obfuscated using various techniques and may be dynamically fetched from attacker-controlled sources. The malicious code does not exfiltrate credentials, establish persistence, or execute arbitrary remote code.
AI Analysis
Technical Summary
This threat involves a family of over 100 near-identical forks of the Baileys WhatsApp Web library, including the @xayz/baileys npm package versions 3.0.0 through 6.1.8. These packages inject code into the WhatsApp socket layer that issues an authenticated 'w:mex' FOLLOW query to attacker-chosen WhatsApp Channel/Newsletter JIDs shortly after connection. The target JIDs are hidden via obfuscation or dynamically fetched from remote sources, enabling attackers to silently subscribe victims' WhatsApp accounts to channels without their knowledge. The attack leverages the installer's authenticated WhatsApp session but does not steal credentials, maintain persistence, or run arbitrary code.
Potential Impact
The impact is unauthorized subscription of the victim's WhatsApp account to attacker-controlled channels, potentially leading to unwanted content delivery or spam. There is no credential theft, no persistence established, and no arbitrary code execution. The attack abuses the victim's authenticated session to increase reach for attacker channels.
Mitigation Recommendations
No official patch or remediation is indicated in the provided data. Users should avoid installing or updating to the affected versions of the @xayz/baileys package listed. Review dependencies carefully and source packages from trusted repositories. Monitor for suspicious channel subscriptions on WhatsApp accounts. Patch status is not yet confirmed — check the vendor advisory for current remediation guidance.
Malicious code in @xayz/baileys (npm)
Description
The @xayz/baileys npm package, a fork of the Baileys WhatsApp Web library, contains malicious code that silently subscribes the victim's WhatsApp account to attacker-controlled channels without user consent. This is done by injecting a covert FOLLOW query into the WhatsApp socket connection using the installer's authenticated session. The target channels are obfuscated using various techniques and may be dynamically fetched from attacker-controlled sources. The malicious code does not exfiltrate credentials, establish persistence, or execute arbitrary remote code.
Affected software
Run on your own infrastructure? Check whether these packages are installed with threat-finder — our free open-source scanner.
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
This threat involves a family of over 100 near-identical forks of the Baileys WhatsApp Web library, including the @xayz/baileys npm package versions 3.0.0 through 6.1.8. These packages inject code into the WhatsApp socket layer that issues an authenticated 'w:mex' FOLLOW query to attacker-chosen WhatsApp Channel/Newsletter JIDs shortly after connection. The target JIDs are hidden via obfuscation or dynamically fetched from remote sources, enabling attackers to silently subscribe victims' WhatsApp accounts to channels without their knowledge. The attack leverages the installer's authenticated WhatsApp session but does not steal credentials, maintain persistence, or run arbitrary code.
Potential Impact
The impact is unauthorized subscription of the victim's WhatsApp account to attacker-controlled channels, potentially leading to unwanted content delivery or spam. There is no credential theft, no persistence established, and no arbitrary code execution. The attack abuses the victim's authenticated session to increase reach for attacker channels.
Mitigation Recommendations
No official patch or remediation is indicated in the provided data. Users should avoid installing or updating to the affected versions of the @xayz/baileys package listed. Review dependencies carefully and source packages from trusted repositories. Monitor for suspicious channel subscriptions on WhatsApp accounts. Patch status is not yet confirmed — check the vendor advisory for current remediation guidance.
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- MAL-2026-17384
- Osv Schema Version
- 1.7.4
- Ecosystems
- ["npm"]
Threat ID: 6abd30852a4e24523d34012e
Added to database: 09/30/2026, 15:53:41 UTC
Last enriched: 09/30/2026, 16:03:12 UTC
Last updated: 09/30/2026, 22:38:54 UTC
Views: 2
Community Reviews
0 reviewsCrowdsource mitigation strategies, share intel context, and vote on the most helpful responses. Sign in to add your voice and help keep defenders ahead.
Want to contribute mitigation steps or threat intel context? Sign in or create an account to join the community discussion.
Actions
Updates to AI analysis require Pro Console access. Upgrade inside Console → Billing.
External Links
Need more coverage?
Upgrade to Pro Console for AI refresh and higher limits.
For incident response and remediation, OffSeq services can help resolve threats faster.
Latest Threats
Check if your credentials are on the dark web
Instant breach scanning across billions of leaked records. Free tier available.