Malicious code in @rennnpm/baileys (npm)
The @rennnpm/baileys npm package version 1.0.0 is a malicious fork of the Baileys WhatsApp Web library that injects code to silently subscribe the victim's WhatsApp account to attacker-controlled channels without user consent. This is done by issuing an authenticated 'w:mex' 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 exfiltrate credentials, establish persistence, or execute arbitrary remote code.
AI Analysis
Technical Summary
The @rennnpm/baileys package (version 1.0.0) is part of a large family of over 100 near-identical malicious forks of the Baileys WhatsApp Web library. These forks inject a covert channel-subscription action into the WhatsApp socket layer. Upon connection, the injected code issues an authenticated 'w:mex' FOLLOW query with a specific query_id against attacker-chosen WhatsApp Channel/Newsletter JIDs, subscribing the victim's account to these channels silently. The target JIDs are hidden using obfuscation techniques such as plain strings, base64 encoding, base64+XOR, char-code arrays, or fetched dynamically from attacker-controlled remote sources. The mechanism relies on wrapping or patching the socket-connect routine to trigger the FOLLOW query shortly after connection. The malicious action leverages the installer's authenticated WhatsApp session but does not steal credentials, maintain persistence, or run arbitrary code remotely.
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, persistence, or arbitrary code execution involved. This misuse of the authenticated session could affect user privacy and trust but does not directly compromise account credentials or device integrity.
Mitigation Recommendations
No official patch or remediation is currently documented. Users should avoid installing or using the @rennnpm/baileys package version 1.0.0. Review and verify the integrity and source of Baileys library forks before use. Since this is a malicious package on npm, removing the package and replacing it with the official Baileys library from trusted sources is recommended. Monitor for updates from the official Baileys project or npm advisories for further guidance.
Malicious code in @rennnpm/baileys (npm)
Description
The @rennnpm/baileys npm package version 1.0.0 is a malicious fork of the Baileys WhatsApp Web library that injects code to silently subscribe the victim's WhatsApp account to attacker-controlled channels without user consent. This is done by issuing an authenticated 'w:mex' 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 exfiltrate credentials, establish persistence, or execute arbitrary remote code.
Affected software
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AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
The @rennnpm/baileys package (version 1.0.0) is part of a large family of over 100 near-identical malicious forks of the Baileys WhatsApp Web library. These forks inject a covert channel-subscription action into the WhatsApp socket layer. Upon connection, the injected code issues an authenticated 'w:mex' FOLLOW query with a specific query_id against attacker-chosen WhatsApp Channel/Newsletter JIDs, subscribing the victim's account to these channels silently. The target JIDs are hidden using obfuscation techniques such as plain strings, base64 encoding, base64+XOR, char-code arrays, or fetched dynamically from attacker-controlled remote sources. The mechanism relies on wrapping or patching the socket-connect routine to trigger the FOLLOW query shortly after connection. The malicious action leverages the installer's authenticated WhatsApp session but does not steal credentials, maintain persistence, or run arbitrary code remotely.
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, persistence, or arbitrary code execution involved. This misuse of the authenticated session could affect user privacy and trust but does not directly compromise account credentials or device integrity.
Mitigation Recommendations
No official patch or remediation is currently documented. Users should avoid installing or using the @rennnpm/baileys package version 1.0.0. Review and verify the integrity and source of Baileys library forks before use. Since this is a malicious package on npm, removing the package and replacing it with the official Baileys library from trusted sources is recommended. Monitor for updates from the official Baileys project or npm advisories for further guidance.
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- MAL-2026-17374
- Osv Schema Version
- 1.7.4
- Ecosystems
- ["npm"]
Threat ID: 6abd30852a4e24523d340164
Added to database: 09/30/2026, 15:53:41 UTC
Last enriched: 09/30/2026, 16:04:23 UTC
Last updated: 09/30/2026, 22:39:50 UTC
Views: 2
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