Malicious code in @kelvdra/baileys (npm)
The @kelvdra/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 achieved by injecting a covert FOLLOW query into the WhatsApp socket connection using the installer's authenticated session. The targeted channel JIDs are obfuscated or dynamically fetched to evade detection. The malicious code does not steal credentials, maintain persistence, or execute arbitrary code remotely.
AI Analysis
Technical Summary
This threat involves a malicious modification in the @kelvdra/baileys npm package versions 1.0.6-rc.1, 1.0.6, and 1.0.5-rc.3. The injected code hooks into the WhatsApp socket connection and 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 targeted JIDs are hidden through various obfuscation methods or fetched dynamically from attacker-controlled remote sources, allowing the attacker to modify targets post-installation. This behavior leverages the victim's authenticated WhatsApp session but does not exfiltrate credentials, establish persistence, or enable remote code execution.
Potential Impact
The impact is limited to 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 mechanism, or arbitrary code execution involved according to the provided data.
Mitigation Recommendations
No patch or official remediation is indicated in the provided data. Users should avoid installing or using the affected versions of the @kelvdra/baileys package (1.0.6-rc.1, 1.0.6, 1.0.5-rc.3). Since no vendor advisory or patch information is available, check for updates or official advisories from the package maintainers or npm registry. Consider auditing dependencies for malicious forks and avoid untrusted sources.
Malicious code in @kelvdra/baileys (npm)
Description
The @kelvdra/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 achieved by injecting a covert FOLLOW query into the WhatsApp socket connection using the installer's authenticated session. The targeted channel JIDs are obfuscated or dynamically fetched to evade detection. The malicious code does not steal credentials, maintain persistence, or execute arbitrary code remotely.
Affected software
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AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
This threat involves a malicious modification in the @kelvdra/baileys npm package versions 1.0.6-rc.1, 1.0.6, and 1.0.5-rc.3. The injected code hooks into the WhatsApp socket connection and 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 targeted JIDs are hidden through various obfuscation methods or fetched dynamically from attacker-controlled remote sources, allowing the attacker to modify targets post-installation. This behavior leverages the victim's authenticated WhatsApp session but does not exfiltrate credentials, establish persistence, or enable remote code execution.
Potential Impact
The impact is limited to 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 mechanism, or arbitrary code execution involved according to the provided data.
Mitigation Recommendations
No patch or official remediation is indicated in the provided data. Users should avoid installing or using the affected versions of the @kelvdra/baileys package (1.0.6-rc.1, 1.0.6, 1.0.5-rc.3). Since no vendor advisory or patch information is available, check for updates or official advisories from the package maintainers or npm registry. Consider auditing dependencies for malicious forks and avoid untrusted sources.
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- MAL-2026-17362
- Osv Schema Version
- 1.7.4
- Ecosystems
- ["npm"]
Threat ID: 6abd30852a4e24523d3401ae
Added to database: 09/30/2026, 15:53:41 UTC
Last enriched: 09/30/2026, 16:05:52 UTC
Last updated: 09/30/2026, 22:41:08 UTC
Views: 4
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