Malicious code in @lendxntaa/baileys (npm)
The @lendxntaa/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 channel-subscription action into the WhatsApp socket layer, issuing an authenticated FOLLOW query using the victim's own WhatsApp session. The target channels are obfuscated or dynamically fetched to evade detection. The malicious code does not steal credentials, maintain persistence, or execute arbitrary code.
AI Analysis
Technical Summary
This threat involves a malicious fork of the Baileys WhatsApp Web library named @lendxntaa/baileys, which injects code into the WhatsApp socket connection process. Upon connection, the injected code issues an authenticated 'w:mex' FOLLOW query to attacker-chosen WhatsApp Channel/Newsletter JIDs, subscribing the victim's account to these channels without their knowledge. The target JIDs are hidden using various obfuscation methods or fetched dynamically from remote sources, allowing attackers to modify targets post-installation. The attack leverages the installer's authenticated WhatsApp session but does not exfiltrate credentials or execute arbitrary remote code. Affected versions include 9.5.0, 9.3.0, 9.1.0, 9.0.2, and 9.0.1 of the package.
Potential Impact
The impact is unauthorized subscription of the victim's WhatsApp account to attacker-controlled channels, potentially leading to unwanted content delivery and privacy concerns. There is no credential theft, persistence, or remote code execution involved. The attack abuses the victim's authenticated session to increase reach for attacker channels.
Mitigation Recommendations
No official patch or remediation guidance is provided in the input data. Users should avoid using the affected versions of the @lendxntaa/baileys package. Since this is a malicious fork, replacing it with the official Baileys library or verified packages is recommended. Patch status is not yet confirmed — check the vendor advisory or trusted sources for current remediation guidance.
Malicious code in @lendxntaa/baileys (npm)
Description
The @lendxntaa/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 channel-subscription action into the WhatsApp socket layer, issuing an authenticated FOLLOW query using the victim's own WhatsApp session. The target channels are obfuscated or dynamically fetched to evade detection. The malicious code does not steal credentials, maintain persistence, or execute arbitrary 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 malicious fork of the Baileys WhatsApp Web library named @lendxntaa/baileys, which injects code into the WhatsApp socket connection process. Upon connection, the injected code issues an authenticated 'w:mex' FOLLOW query to attacker-chosen WhatsApp Channel/Newsletter JIDs, subscribing the victim's account to these channels without their knowledge. The target JIDs are hidden using various obfuscation methods or fetched dynamically from remote sources, allowing attackers to modify targets post-installation. The attack leverages the installer's authenticated WhatsApp session but does not exfiltrate credentials or execute arbitrary remote code. Affected versions include 9.5.0, 9.3.0, 9.1.0, 9.0.2, and 9.0.1 of the package.
Potential Impact
The impact is unauthorized subscription of the victim's WhatsApp account to attacker-controlled channels, potentially leading to unwanted content delivery and privacy concerns. There is no credential theft, persistence, or remote code execution involved. The attack abuses the victim's authenticated session to increase reach for attacker channels.
Mitigation Recommendations
No official patch or remediation guidance is provided in the input data. Users should avoid using the affected versions of the @lendxntaa/baileys package. Since this is a malicious fork, replacing it with the official Baileys library or verified packages is recommended. Patch status is not yet confirmed — check the vendor advisory or trusted sources for current remediation guidance.
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- MAL-2026-17365
- Osv Schema Version
- 1.7.4
- Ecosystems
- ["npm"]
Threat ID: 6abd30852a4e24523d3401ab
Added to database: 09/30/2026, 15:53:41 UTC
Last enriched: 09/30/2026, 16:05:26 UTC
Last updated: 09/30/2026, 22:40:53 UTC
Views: 4
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.