Malicious code in @saazkira/baileys (npm)
The @saazkira/baileys npm package versions 2.1.6 through 2.1.9 contain malicious code that silently subscribes the victim's WhatsApp account to attacker-controlled channels without user consent. This is done by injecting a covert subscription action into the WhatsApp socket layer, leveraging the installer's authenticated session to issue a FOLLOW query to attacker-chosen WhatsApp Channel JIDs. The targeted JIDs are obfuscated or fetched remotely to evade detection. 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 malicious forks of the Baileys WhatsApp Web library, including the @saazkira/baileys npm package versions 2.1.6 to 2.1.9. The injected code patches the WhatsApp socket connect routine to issue an authenticated 'w:mex' FOLLOW query to attacker-controlled WhatsApp Channel JIDs shortly after connection. The victim's authenticated WhatsApp session is abused to silently subscribe their account to these channels. The target JIDs are hidden via obfuscation methods such as base64 encoding, XOR, or runtime reconstruction, or fetched dynamically from attacker-controlled remote sources. The malicious action is limited to subscription abuse and does not involve credential theft, persistence, or arbitrary code execution.
Potential Impact
Victims unknowingly subscribe their WhatsApp accounts to attacker-controlled channels or newsletters, potentially exposing them to unwanted content or spam. The attack leverages the victim's authenticated session but does not compromise credentials or allow further remote code execution or persistence. The impact is primarily unauthorized subscription and potential privacy or spam concerns.
Mitigation Recommendations
No official patch or remediation guidance is provided in the available data. Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. Users should avoid installing or using the affected versions of the @saazkira/baileys package (2.1.6 to 2.1.9) and verify the integrity of their dependencies. Consider using trusted package sources and scanning for malicious code in dependencies.
Malicious code in @saazkira/baileys (npm)
Description
The @saazkira/baileys npm package versions 2.1.6 through 2.1.9 contain malicious code that silently subscribes the victim's WhatsApp account to attacker-controlled channels without user consent. This is done by injecting a covert subscription action into the WhatsApp socket layer, leveraging the installer's authenticated session to issue a FOLLOW query to attacker-chosen WhatsApp Channel JIDs. The targeted JIDs are obfuscated or fetched remotely 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
This threat involves a family of over 100 near-identical malicious forks of the Baileys WhatsApp Web library, including the @saazkira/baileys npm package versions 2.1.6 to 2.1.9. The injected code patches the WhatsApp socket connect routine to issue an authenticated 'w:mex' FOLLOW query to attacker-controlled WhatsApp Channel JIDs shortly after connection. The victim's authenticated WhatsApp session is abused to silently subscribe their account to these channels. The target JIDs are hidden via obfuscation methods such as base64 encoding, XOR, or runtime reconstruction, or fetched dynamically from attacker-controlled remote sources. The malicious action is limited to subscription abuse and does not involve credential theft, persistence, or arbitrary code execution.
Potential Impact
Victims unknowingly subscribe their WhatsApp accounts to attacker-controlled channels or newsletters, potentially exposing them to unwanted content or spam. The attack leverages the victim's authenticated session but does not compromise credentials or allow further remote code execution or persistence. The impact is primarily unauthorized subscription and potential privacy or spam concerns.
Mitigation Recommendations
No official patch or remediation guidance is provided in the available data. Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. Users should avoid installing or using the affected versions of the @saazkira/baileys package (2.1.6 to 2.1.9) and verify the integrity of their dependencies. Consider using trusted package sources and scanning for malicious code in dependencies.
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- MAL-2026-17377
- Osv Schema Version
- 1.7.4
- Ecosystems
- ["npm"]
Threat ID: 6abd30852a4e24523d34014b
Added to database: 09/30/2026, 15:53:41 UTC
Last enriched: 09/30/2026, 16:04:05 UTC
Last updated: 09/30/2026, 22:39:38 UTC
Views: 2
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