No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by Enriquefft · Agent Tool · ★ 206
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is openclaw-kapso-whatsapp safe to install? View the security audit →
openclaw-kapso-whatsapp Give your OpenClaw AI agent a WhatsApp number. Official Meta Cloud API via Kapso — a unified API for WhatsApp Cloud. No ban risk. Stateless. Two Go binaries. Near-zero idle CPU. Architecture Libraries like Baileys and whatsapp-web.js reverse-engineer WhatsApp Web — Meta actively detects and bans these connections. This bridge uses the official Cloud API through Kapso, so your number stays safe. Stateless API calls, no session management, near-zero idle CPU. Table of contents Installation Quick start [Confi
| Stars | 206 |
| Forks | 24 |
| Language | Go |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 74.6252077308011/100 |
| Open Issues | 7 |
| Last Updated | 2026-03-29 |
| Created | 2026-02-28 |
| Platforms | go |
| Est. Tokens | ~434k |
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openclaw-kapso-whatsapp is Give your OpenClaw AI agent a WhatsApp number. Official Meta Cloud API via Kapso. No ban risk.. It is categorized as a Agent Tool with 206 GitHub stars.
openclaw-kapso-whatsapp is primarily written in Go. It covers topics such as ai, chatbot, go.
You can find installation instructions and usage details in the openclaw-kapso-whatsapp GitHub repository at github.com/Enriquefft/openclaw-kapso-whatsapp. The project has 206 stars and 24 forks, indicating an active community.
openclaw-kapso-whatsapp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to openclaw-kapso-whatsapp on Agent Skills Hub include whatsapp-agentkit, awesome-openclaw, Wegent. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: