I built ClawMon. A monitor for unsafe OpenClaw instances
Summary
The author developed ClawMon, a monitoring tool for unsafe OpenClaw instances, highlighting significant security and economic issues within the OpenClaw ecosystem. Despite its rapid adoption, with 234,000 GitHub stars in three months since its November 2025 release, OpenClaw exhibits a 36% malware rate among its instances. One in five ClawHub skills contains malicious code, often disguised as documentation in SKILL.md files, which traditional antivirus software fails to detect. The framework's most transformative applications require deep system access, creating an "existential security nightmare." Furthermore, economic changes, specifically Anthropic and Google revoking OAuth access, have increased operational costs from approximately $20/month to over $100/month, while OpenAI maintained access.
Key takeaway
For CTOs and VPs of Engineering evaluating OpenClaw for agentic applications, you must prioritize a thorough security audit of all integrated skills and monitor for hidden malware. The significant malware rate and the potential for disguised installers in SKILL.md files necessitate advanced threat detection beyond standard antivirus. Additionally, factor in the increased operational costs due to changes in OAuth access from major providers when planning your budget and infrastructure.
Key insights
OpenClaw's rapid adoption masks critical security vulnerabilities and escalating operational costs.
Principles
- Deep system access amplifies security risks.
- Community innovation requires robust guardrails.
Method
ClawMon monitors OpenClaw instances to identify and flag unsafe configurations and malicious skill integrations, addressing the limitations of traditional antivirus.
In practice
- Scrutinize OpenClaw skills for hidden installers.
- Evaluate cost implications of OAuth access changes.
Topics
- OpenClaw
- AI Agents
- Malware
- Cybersecurity
- AI Economics
Best for: CTO, VP of Engineering/Data, Director of AI/ML, AI Security Engineer, AI Engineer, MLOps Engineer
Related on AIssential
Editorial summary, takeaway, and curation by AIssential. Original article published by AI Advances - Medium.