# Introduction
Open Claw 2026 is one of the most powerful open source autonomous agent frameworks available. It’s not just a chatbot layer. It runs the gateway process, installs executable skills, connects to external tools, and can perform actual actions on your system and messaging platforms.
This capability is exactly what makes OpenClaw different, and also makes it important to approach it with the same mindset you’ll apply to running the infrastructure.
Once you start enabling skills, exposing a gateway, or giving an agent access to files, secrets, and plugins, you’re doing something that poses a real security and operational risk.
Before deploying 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 configure it securely.
# 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’re running something that can be attacked.
Do this quickly:
- Just keep it locally unless you trust your configuration.
- Check the log and recent sessions for unexpected tool calls.
- Run the built-in audit again after making 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 talent can run commands, access files, trigger workflows, and interact directly with your system. This 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, which often rely on social engineering to trick users into running insecure 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 might see results like this:
- Security Scan: Benazir
- Virus Total: View the report
- OpenClaw Classification: Doubtful (high confidence)
Always take these warnings seriously, especially if a skill has been flagged as suspicious.
Principles of Practice:
- Install fewer skills at first, only from trusted authors
- Always read the skill documentation and repository before running it
- Be wary of any skills that ask you to paste long or confusing shell commands.
- Check security scan and virus total report before downloading.
- Keep everything updated regularly:
# 3. Always use a robust model.
The security and reliability of OpenClaw is highly dependent on the model you connect to. Because OpenClaw can run tools and perform real operations, the model is not just generating text. It’s making decisions that can affect your system.
A weak model can:
- Misfire tool calls
- Follow the unguarded instructions.
- Start doing things you didn’t intend to do.
- Get confused when there are multiple tools available.
Use top-tier, toolable models. In 2026, the most consistently robust options for agent workflow and coding include:
- Cloud Ops 4.6 For planning, reliability, and agent-style work
- GPT-5.3-Codex For agentive coding and long-running tool tasks
- GLM-5 If you want a longer horizon and a strong open source leaning option focused on agent capability.
- Kimi K2.5 For multimodal and agent workflows, including extensive task execution features
Principles of practical setting:
- Prefer official provider integrations when possible, as they usually have better streaming and tool support.
- Avoid experimental or low-quality models when the tools are active.
- Continue clear routing. Decide which tasks are enabled by the tool and which are text-only, so you don’t accidentally grant high-permission access to the wrong model.
If privacy is your priority, a common starting point is running OpenClaw natively with Ulama:
# 4. Lockdown secrets and your workplace
The biggest real-world threat isn’t just bad skills. There is a big risk. Display of Credentials.
OpenClaw often ends up sitting with your most sensitive assets: API keys, access tokens, SSH credentials, browser sessions, and configuration files. If any of these are leaked, the attacker does not need to break the model. They just need to reuse your credentials.
Treat secrets as high-value goals:
- 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 secret managers, not inside skill configurations or plain text files
- Keep your OpenClaw workspace minimal. Do not mount your entire home directory.
- Restrict file permissions on the OpenClaw workspace so that only the agent user can access it.
- If you ever install something suspicious or see unexpected tool calls, rotate the token immediately
- Prefer solitude to anything serious. Run OpenCloud inside a container or isolated VM so that a compromised skill cannot access the rest of your machine.
If you’re running OpenClaw on a shared server, treat it like a production infrastructure. Least privilege is the difference between a secure agent and a full account takeover.
# 5. Voice calls are a real global power… and threat
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 just answering in chat. It is talking directly to people.
This is a great potential, but it also introduces a high level of operational and financial risk.
Before enabling voice calling, you must define clear boundaries:
- Who can be called, when and for what purpose.
- What an agent is allowed to say during a live chat.
- How do you prevent accidental call loops, spam behavior, or unexpected usage charges?
- Whether human approval is required before making calls.
Voice tools should always be treated as high-permission operations like 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 actionable skills, automate workflows, and operate over messaging and voice channels.
This is why it should be treated with caution.
If you approach an infrastructure like OpenClaw, keep expertise to a minimum, choose a robust model, lock down secrets, and only enable high-permission plugins with clear controls, it becomes a very powerful platform for building truly autonomous systems.
The future of AI agents is not just about intelligence. It’s about implementation, trust and security. OpenClaw gives you the power to create that future, but it’s 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 create an AI product using graph neural networks for students struggling with mental illness.