What Are the Security Risks of OpenClaw?

Understanding the risks helps you mitigate them effectively. OpenClaw is designed with security in mind, but like any powerful tool, it has an attack surface.

Prompt injection: Malicious content in web pages, emails, or messages could trick the agent into performing unintended actions. OpenClaw includes prompt injection detection, but it's not foolproof. Mitigation: enable skill sandboxing, limit the agent's permissions.

API key exposure: If your config file or environment is compromised, attackers could use your API keys. Mitigation: restrict file permissions, use environment variables, rotate keys regularly.

Skill supply chain: Community skills from ClawHub could contain malicious code. Mitigation: review skill source code, check download counts and reviews, use the skill auditing tools.

Data leakage: Conversations are sent to the AI model provider's API. Mitigation: use local models via Ollama for sensitive data, review the provider's data policy.

Overprivileged agent: An agent with too many skills and permissions could cause damage if it misinterprets a command. Mitigation: apply the principle of least privilege — only install needed skills, restrict filesystem access.

Gateway exposure: An exposed Gateway without authentication could be accessed by attackers. Mitigation: always use the Gateway token, restrict network access.

Most risks are manageable with the best practices outlined in our security guide. The self-hosted nature of OpenClaw actually reduces many risks compared to cloud-based AI services.