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# Introduction
OpenClaw is one of the most powerful open source autonomous agent frameworks available in 2026. It is not just a chatbot layer. It runs a Gateway process, installs executable skills, connects to external tools, and can take real actions across your system and messaging platforms.
That capability is exactly what makes OpenClaw different, and also what makes it important to approach with the same mindset you would apply to running infrastructure.
Once you start enabling skills, exposing a gateway, or giving an agent access to files, secrets, and plugins, you are operating something that carries real security and operational risk.
Before you deploy OpenClaw locally or in production, here are five essential things you need to understand about how it works, where the biggest risks are, and how to set it up safely.
# 1. Treat It Like a Server, Because It Is One
OpenClaw runs a Gateway process that connects channels, tools, and models. The moment you expose it to a network, you are running something that can be attacked.
Do this early:
- Keep it local-only until you trust your configuration
- Check logs and recent sessions for unexpected tool calls
- Re-run the built-in audit after changes
Run:
openclaw security audit –deep
# 2. OpenClaw Skills Are Code, Not “Add-ons”
ClawHub is where most people discover and install OpenClaw skills. But the most important thing to understand is simple:
Skills are executable code.
They are not harmless plugins. A skill can run commands, access files, trigger workflows, and interact directly with your system. That makes them extremely powerful, but it also introduces real supply-chain risk.
Security researchers have already reported malicious skills being uploaded to registries like ClawHub, often relying on social engineering to trick users into running unsafe commands.
The good news is that ClawHub now includes built-in security scanning, including VirusTotal reports, so you can review a skill before installing it. For example, you may see results like:
- Security Scan: Benign
- VirusTotal: View report
- OpenClaw Rating: Suspicious (high confidence)
Always treat these warnings seriously, especially if a skill is flagged as suspicious.
Practical rules:
- Install fewer skills at the start, only from trusted authors
- Always read the skill documentation and repository before running it
- Be cautious of any skill that asks you to paste long or obfuscated shell commands
- Check the security scan and VirusTotal report before downloading
- Keep everything updated regularly:
# 3. Always Use a Strong Model
OpenClaw’s safety and reliability depend heavily on the model you connect to it. Since OpenClaw can execute tools and take real actions, the model is not only generating text. It is making decisions that can affect your system.
A weak model can:
- Misfire tool calls
- Follow unsafe instructions
- Trigger actions you did not intend
- Get confused when multiple tools are available
Use a top tier, tool-capable model. In 2026, the most consistently strong options for agent workflows and coding include:
- Claude Opus 4.6 for planning, reliability, and agent style work
- GPT-5.3-Codex for agentic coding and long-running tool tasks
- GLM-5 if you want a strong open-source leaning option focused on long-horizon and agent capability
- Kimi K2.5 for multimodal and agentic workflows, including larger task execution features
Practical setup rules:
- Prefer official provider integrations when possible, because they usually have better streaming and tool support
- Avoid experimental or low-quality models when tools are enabled
- Keep routing explicit. Decide which tasks are tool-enabled and which are text-only, so you do not accidentally grant high-permission access to the wrong model
If privacy is your priority, a common starting point is running OpenClaw locally with Ollama:
# 4. Lock Down Secrets And Your Workspace
The biggest real world risk is not only bad skills. The bigger risk is credential exposure.
OpenClaw often ends up sitting next to your most sensitive assets: API keys, access tokens, SSH credentials, browser sessions, and configuration files. If any of those leak, an attacker does not need to break the model. They only need to reuse your credentials.
Treat secrets as high value targets:
- API keys and provider tokens
- Slack, Telegram, WhatsApp sessions
- GitHub tokens and deployment keys
- SSH keys and cloud credentials
- Browser cookies and saved sessions
Do this in practice:
- Store secrets in environment variables or a secrets manager, not inside skill configs or plain text files
- Keep your OpenClaw workspace minimal. Do not mount your whole home directory
- Restrict file permissions on the OpenClaw workspace so only the agent user can access it
- Rotate tokens immediately if you ever install something suspicious or see unexpected tool calls
- Prefer isolation for anything serious. Run OpenClaw inside a container or an isolated VM so a compromised skill cannot access the rest of your machine
If you are running OpenClaw on any shared server, treat it like production infrastructure. Least privilege is the difference between a safe agent and a full account takeover.
# 5. Voice Calls Are Real-World Power… And Risk
The Voice Call plugin takes OpenClaw beyond text and into the real world. It enables outbound phone calls and multi turn voice conversations, which means your agent is no longer only responding in chat. It is speaking directly to people.
That is a major capability, but it also introduces a higher level of operational and financial risk.
Before enabling voice calling, you should define clear boundaries:
- Who can be called, when, and for what purpose
- What the agent is allowed to say during a live conversation
- How you prevent accidental call loops, spam behavior, or unexpected usage costs
- Whether calls require human approval before being placed
Voice tools should always be treated as high permission actions, similar to payment or admin access.
# Final Thoughts
OpenClaw is one of the most capable open source agent frameworks available today. It can connect to real tools, install executable skills, automate workflows, and operate across messaging and voice channels.
That is exactly why it should be treated with care.
If you approach OpenClaw like infrastructure, keep skills minimal, choose a strong model, lock down secrets, and enable high permission plugins only with clear controls, it becomes an extremely powerful platform for building real autonomous systems.
The future of AI agents is not only about intelligence. It is about execution, trust, and safety. OpenClaw gives you the power to build that future, but it is your responsibility to deploy it intentionally.
Abid Ali Awan (@1abidaliawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master’s degree in technology management and a bachelor’s degree in telecommunication engineering. His vision is to build an AI product using a graph neural network for students struggling with mental illness.
