This blog covers what’s going on with OpenClaw mania, the security risks people overlook to start experimenting with OpenClaw as quickly as possible, and how you can access your OpenClaw deployment from anywhere without sacrificing speed or security.

In the last week of January 2026, everything was coming up OpenClaw. 

OpenClaw (formerly ClawdBot/MoltBot) is an open-source AI assistant that can read your emails, control your smart home, and manage your calendar. In late January, it seemed to take over the tech side of the internet.

The excitement got another boost when Peter Steinberger, the human brain behind OpenClaw, announced he’d be joining OpenAI while spinning OpenClaw out into an independent foundation, with OpenAI sponsoring the project.

And honestly? The excitement makes sense. OpenClaw is one of the first AI assistants that feels like it can potentially deliver on what AI companies have been promising for months: actually doing useful things instead of just suggesting them. 

OpenClaw integrates with Slack, manages calendars, controls smart home devices, and executes code. When it works, it's genuinely impressive. When it doesn't (and let's be honest, it goes off the rails pretty frequently) it's a reminder that we're still in the early experimental phase of AI agents.

Even with its quirks and limitations, OpenClaw points at something important: a future where AI assistants can actually take action on your behalf and finally eliminate the countless administrative tasks that get on your nerves. 

That's what has developers excited enough to experiment, even when it means dealing with the occasional chaos.

The catch? With great power comes great security headaches.

The Mac mini madness

If you were following the OpenClaw madness live, you probably noticed a pattern in the hype posts: a lot of people ran out and bought dedicated Mac minis to run it.

Why? Because giving an AI agent, especially one that’s still rough around the edges, the keys to your actual development machine feels risky. 

Your dev machine has your SSH keys, AWS credentials, GitHub tokens, production database access, and browser sessions with active auth tokens. Running experimental AI software with broad system access on that same machine is a recipe for anxiety.

OpenClaw is designed to have deep system access. It needs to execute commands, read files, manage processes, and integrate with everything. That's what makes it powerful. It's also what makes a compromise devastating.

And compromises happen. Within days of OpenClaw's explosion in popularity, security researchers found:

• A critical 1-click RCE vulnerability that could grant attackers complete system control via a malicious link

• 341 malicious skills on ClawHub distributing infostealers and trojans disguised as legitimate integrations

• Over 21,000 publicly exposed instances running default configurations on the open internet

The Mac mini strategy makes sense: air-gap your AI experiments from your actual infrastructure. It creates a boundary between OpenClaw and everything else on your network.

There's a better approach.

Cloud deployment: Isolation without the hardware

Instead of buying a Mac mini, you should just deploy OpenClaw to an isolated cloud instance. You get all the isolation benefits without the hardware investment:

Complete separation: Your SSH keys, AWS credentials, local repositories, browser sessions, and password managers stay on your dev machine. The cloud instance only has what you explicitly give it.

Controlled blast radius: If OpenClaw gets compromised, the attacker only gets what's on that VPS. Not your entire local development environment.

Clean credential management: Give the cloud instance only the specific API keys and permissions it needs. No ambient authority from running on a machine with access to everything.

Easy to rebuild: Something goes wrong? Destroy the droplet and spin up a fresh one in minutes. No need to wipe and reinstall your local machine.

No shared filesystem: Unlike running locally where OpenClaw could potentially access any file on your system, the cloud instance only has what you explicitly put there.

This is the Mac mini strategy, evolved: same isolation benefits, better flexibility, lower cost.

That said, you can run OpenClaw locally or on a dedicated Mac mini with Twingate. The security model works the same way. But for most use cases, we recommend cloud deployment for the isolation benefits.

OpenClaw away from home

Here's what actually happens when you deploy OpenClaw to the cloud:

You spin up a DigitalOcean droplet (or AWS/Azure/GCP instance - we like DigitalOcean because it’s cost-effective and user friendly). You get OpenClaw running. Everything works great when you SSH in. 

Then you want to access it from your phone, or your laptop when you're traveling, or you want to share it with your team.

So you do one of these:

• Expose port 18789 to the internet (please don't)

• Set up an SSH tunnel every time you want to connect (works but is annoying)

• Put it behind Cloudflare Tunnel (better, but still tricky to get right)

• Give up and only use it when you remember to SSH in first

Most people pick option 3 or 4. And even when they pick option 3, they often misconfigure it because the documentation is scattered and the threat model isn't obvious.

When Censys found 21,000+ exposed instances, that wasn’t because 21,000 people didn’t care about security. It's because making it secure and usable is genuinely hard.

OpenClaw from anywhere, done the right way

The core problem is that traditional security approaches make you choose between security and usability:

VPNs give network-wide access to everyone who authenticates. That's fine for browsing internal docs, but do you really want your entire VPN user list to have access to your AI agent that can execute arbitrary commands?

SSH tunnels work great if you're the only user and you don't mind the setup friction. They break down fast when you want to access from mobile, share with teammates, or need fine-grained permissions.

Direct exposure with authentication is what most guides suggest, but then you're trusting that the auth implementation is bulletproof and that nobody's credentials get compromised.

What if you could get the usability of "works everywhere" with the security of "locked down by default"?

That's what Twingate does. It's a zero trust access platform that replaces VPNs and SSH tunnels with secure, direct connections to specific resources, all without exposed ports or network-wide access.

We built multiple deployment guides that take ~15 minutes and give you:

• Zero public exposure: Whether you're running OpenClaw locally or on a cloud instance, no ports get exposed to the internet

• Access from anywhere: Phone, laptop, wherever, without SSH tunnels or VPN headaches

• Actually usable access controls: Want to let your roommate try it without giving them full system access? Easy. Want to access it from your phone but only when you're on a trusted device? Done.

• Audit trails: See exactly when and from where you (or anyone else) accessed your instance

For cloud deployments (recommended):
Read the guide →

1. OpenClaw runs on an isolated cloud instance with no inbound ports exposed

2. The Twingate Connector on the same instance creates an outbound-only secure connection to Twingate Cloud

3. You connect via Twingate Client from any device with Zero Trust policies

4. Complete isolation from your local dev environment—the cloud instance only has the credentials and access you explicitly grant

For local deployments:
Read the guide →

1. OpenClaw runs on localhost:18789 on your machine (or on a dedicated Mac mini)

2. Twingate Connector creates an outbound-only secure connection

3. Same secure access model from any device

4. Good for testing, but less isolation than cloud deployment

No exposed ports. No complex firewall rules. No choosing between security and convenience.

The agentic iceberg is here

OpenClaw isn't a polished product. It's experimental software that breaks frequently and does unexpected things. But it feels different from other AI demos because it's actually trying to be autonomous.

For the first time, an AI agent actually feels like the future people have been promising: proactive, autonomous, integrated into your actual workflows. Not a chatbot that suggests code. A thing that writes code, tests it, deploys it, and fixes the bugs while you sleep. 

The execution can be rough, but the direction is clear.

That's why people are buying Mac minis to experiment, why deployments exploded in a week, and why engineers exhausted by AI hype cycles are actually paying attention this time. 

OpenClaw hints at what’s coming.

OpenClaw is just the most visible example. Below it are thousands of experimental AI agents, automation frameworks, and autonomous systems being built in garages, startups, and enterprises right now.

Each one will need the same capabilities: system access, API credentials, data integration, execution permissions. Each one will create the same security challenges. And each one will face the same choice: build it secure from the start, or bolt on security later when something breaks.

Don’t let security be an afterthought

This is the critical moment. Not just for OpenClaw, but for the entire agentic AI ecosystem that's about to explode.

When you give an AI agent access to your codebase, cloud infrastructure, and communication tools, you're creating a high-privilege automation system that can do everything you can do… For better or for worse.

If that system gets compromised, the attacker gets access to data, just like historical breaches. They also get access capabilities. That means executing commands, accessing secrets, modifying infrastructure, and pivoting through your entire environment.

The traditional security model of "deploy first, secure later" doesn't work when:

• The system has broad permissions by design

• Compromise grants capabilities, not just access

• The attack surface includes third-party integrations (hello, ClawHub)

• Speed of deployment is a competitive advantage

Security has to be baked in from day one. Not because of compliance requirements or risk management frameworks, but because agents that can actually do things are too powerful to leave unsecured.

The good news? It doesn't have to slow you down.

Go forth and build

The AI agent era is happening. OpenClaw proved that people are ready for assistants that actually assist, solve problems, and work autonomously.

It’s an amazing opportunity to experiment, and you absolutely should. You just need to make sure that you do it in a way that lets you move fast and stay secure.

We built the Twingate deployment guide because we kept seeing the same pattern: developers excited about agents, held back by security concerns, making compromises that left them exposed.

It doesn't have to be that way.

Deploy OpenClaw. Play with it. Push it to the limits. Build something wild. Just do it on infrastructure that's actually secure. Not because you're paranoid, but because you're taking it seriously.

Ready to get started?

Read our step-by-step guide → Secure OpenClaw Deployments with Twingate

New to Twingate? You can use Twingate for free for up to 5 users, request a personalized demo, or reach out to the team over on the Twingate subreddit.