Malicious code in @levvicode/baileys (npm)
The @levvicode/baileys npm package versions 0.0.2 and 0.0.3 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 FOLLOW query into the WhatsApp socket connection using the installer's authenticated session. The target channels are obfuscated or dynamically fetched, allowing attackers to change targets post-installation. The malicious code does not steal credentials, maintain 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 @levvicode/baileys npm package versions 0.0.2 and 0.0.3. These forks inject code into the WhatsApp socket layer that 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 through various obfuscation methods or fetched dynamically from attacker-controlled remote sources. The attack leverages the installer's authenticated WhatsApp session but does not exfiltrate credentials, establish persistence, or execute arbitrary code remotely.
Potential Impact
Victims unknowingly subscribe their WhatsApp accounts to attacker-controlled channels, potentially exposing them to unwanted content or spam. The attack does not compromise credentials or allow remote code execution, limiting its impact to unauthorized channel subscriptions.
Mitigation Recommendations
No official patch or remediation is currently documented. Users should avoid installing or using the affected @levvicode/baileys package versions 0.0.2 and 0.0.3. Review dependencies for malicious forks and consider using official or verified Baileys library versions. Monitor for updates from the package maintainers or security advisories for remediation guidance.
Malicious code in @levvicode/baileys (npm)
Description
The @levvicode/baileys npm package versions 0.0.2 and 0.0.3 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 FOLLOW query into the WhatsApp socket connection using the installer's authenticated session. The target channels are obfuscated or dynamically fetched, allowing attackers to change targets post-installation. The malicious code does not steal credentials, maintain 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 @levvicode/baileys npm package versions 0.0.2 and 0.0.3. These forks inject code into the WhatsApp socket layer that 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 through various obfuscation methods or fetched dynamically from attacker-controlled remote sources. The attack leverages the installer's authenticated WhatsApp session but does not exfiltrate credentials, establish persistence, or execute arbitrary code remotely.
Potential Impact
Victims unknowingly subscribe their WhatsApp accounts to attacker-controlled channels, potentially exposing them to unwanted content or spam. The attack does not compromise credentials or allow remote code execution, limiting its impact to unauthorized channel subscriptions.
Mitigation Recommendations
No official patch or remediation is currently documented. Users should avoid installing or using the affected @levvicode/baileys package versions 0.0.2 and 0.0.3. Review dependencies for malicious forks and consider using official or verified Baileys library versions. Monitor for updates from the package maintainers or security advisories for remediation guidance.
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- MAL-2026-17366
- Osv Schema Version
- 1.7.4
- Ecosystems
- ["npm"]
Threat ID: 6abd30852a4e24523d3401aa
Added to database: 09/30/2026, 15:53:41 UTC
Last enriched: 09/30/2026, 16:05:20 UTC
Last updated: 09/30/2026, 22:40:49 UTC
Views: 2
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