kiki-baileys
Whatsapp baileys coded by Fallzx-Coderid.
This report shows the evidence for kiki-baileys@1.0.2. 4 of 5 known versions are blocked or flagged. The newest version, 0.0.1-security, is allowed. See all versions.
This package appears in our research on the malicious Baileys forks, with how it works, the full package list and what to do if you installed it.
AI Security Review
scanned 2mo ago · by lpm-firewall-aiThis package contains concrete, unconsented mutations of a user's WhatsApp subscriptions and message content, plus a reachable shell-injection flaw. These behaviors are unrelated to ordinary messaging-library operation and warrant blocking.
Decision evidence
public snapshot- Creating a WhatsApp socket automatically follows two hard-coded newsletter accounts after a delay.
- The package continuously changes the user's newsletter subscriptions by unfollowing a hard-coded blacklist.
- Media messages without annotations receive a hidden, hard-coded newsletter attribution.
- Video thumbnail generation interpolates a supplied path into a shell command, enabling command injection.
- No credential harvesting or exfiltration to a non-WhatsApp endpoint was found.
- The preinstall hook only invokes a local Node version check; it does not establish the malicious runtime behavior.
Source & flagged code
6 flagged · loading sourcePackage defines install-time lifecycle scripts.
package.jsonView on unpkgPackage contains source files above the normal full-analysis size ceiling.
WAProto/index.jsView on unpkgFindings
Affected versions and remediation
This report applies to kiki-baileys@1.0.2.
The versions list below shows the verdict for each recorded version.
- Avoid installing kiki-baileys@1.0.2. Remove it from direct dependencies and check your lockfile for transitive copies.
- Choose an independently verified alternative or release. This report does not establish that other versions are safe.
- If this version ran, investigate the affected machine and build environment. Rotate credentials it could access and rebuild from a trusted environment.
Evidence last updated: .
Source advisory published: .
Think this verdict is wrong? Dispute it on GitHub or read how reports are produced.