Not an App. OpenClaw is an open-source AI Agent framework / execution AI assistant that runs on your computer or server to execute real tasks, not chat. **Real Talk:** It's basically a junior engineer with sudo privileges.

What's the essential difference from ChatGPT / Claude?

In short: ChatGPT 'thinks', OpenClaw 'does'. ChatGPT: Answers questions, gives advice OpenClaw: Reads files, runs commands, modifies code, executes workflows **Real Talk:** ChatGPT is a consultant. OpenClaw is an intern who actually does the work.

Does OpenClaw have its own LLM?

No. It's a 'scheduler' that needs you to connect: OpenAI, Claude or local models. 👉 It doesn't sell models, just makes models 'work'. **Real Talk:** You're the DJ. OpenClaw is just the mixer.

Is my data private with local models?

**Short answer:** If you use Ollama locally, yes. The model runs on your machine. **How to verify:** Don't take my word for it. Block outbound traffic (except localhost) via Little Snitch or `ufw`. If OpenClaw still talks to your local Ollama, it's local. If it hangs, check your `base_url`. **Caveat:** If you use API providers (DeepSeek, OpenAI, Anthropic), your prompts go to their servers. Read their privacy policies.

Does it support DeepSeek API?

✅ Yes. Set `LLM_PROVIDER=openai` and `BASE_URL=https://api.deepseek.com`. **Config example (.env)**: ```bash LLM_PROVIDER="openai" LLM_BASE_URL="https://api.deepseek.com" LLM_API_KEY="sk-your-key-here" LLM_MODEL="deepseek-reasoner" ``` 👉 See our **[DeepSeek Config Guide](/guides/how-to-use-deepseek-with-openclaw)** for full setup.

Does it support local DeepSeek (Ollama)?

✅ Yes. Use `provider: ollama`. **Config example (.env)**: ```bash # Install Ollama & pull model curl -fsSL https://ollama.com/install.sh | sh ollama run deepseek-r1:8b # Configure OpenClaw LLM_PROVIDER="ollama" LLM_BASE_URL="http://localhost:11434/v1" LLM_MODEL="deepseek-r1:8b" ``` ⚠️ **Warning:** Requires heavy hardware. See **[Hardware Reality Check](/guides/fix-openclaw-cuda-oom-errors)**.

What is the relationship between OpenClaw and Ollama?

**Ollama is the engine; OpenClaw is the driver.** Ollama runs the DeepSeek model (loads it into VRAM, handles inference). OpenClaw tells it what to do (reads files, runs commands, executes workflows). If Ollama is down, OpenClaw is useless. If OpenClaw isn't running, Ollama is just a chatbot. **Analogy:** Ollama = Engine, OpenClaw = Driver. You need both to drive the car.

Do I need to know programming?

Basic use: No coding needed, but need basic logic Advanced use: Knowing some command line/project structure helps 👉 It's not 'zero barrier', but 'low barrier, high ceiling'. **Real Talk:** If you don't know what `chmod +x` means, you're going to have a bad time.

Can it run on Windows / Mac / Linux?

✅ Mac: Most friendly ✅ Linux / Server: First choice for production ⚠️ Windows: Usually via WSL2 (strongly recommended) **Symptom:** `Error: connect ECONNREFUSED 127.0.0.1:11434` (Networking issue) **Real Talk:** Mac users suffer slowly (3.2 tokens/sec). Windows users suffer dramatically (WSL2 drama). Linux users just suffer.

Can OpenClaw run continuously?

Yes. It can: run long-term, retry on failure, save intermediate state, stop by rules. This is why it's called an autonomous agent. **Real Talk:** That's also why it's called a 'security risk'. It doesn't know when to quit.

Why am I getting JSON parsing errors?

DeepSeek R1 wraps responses in `` tags before the actual JSON. OpenClaw's JSON parser fails. **Symptom:** `SyntaxError: Unexpected token <` (The model is 'thinking' out loud) 👉 **Fix it here:** **[JSON Parsing Fix](/guides/fix-openclaw-json-mode-errors)**.

Is OpenClaw safe? How to prevent Prompt Injection?

**Think of OpenClaw as a junior engineer with sudo privileges.** If you wouldn't trust a junior intern with root access to this folder, don't trust the agent. **Real incidents I've stopped:** - Agent tried to `rm -rf .` to "clean build artifacts" - Agent attempted `curl unknown.sh | bash` because it needed a tool **Mitigation**: - Run in Docker container with read-only filesystem - Use dedicated device (Mac Mini, cheap server) - Block dangerous commands (rm, format, dd, etc.) - Review EVERY execution log 👉 **Read the full autopsy:** **[CVE-2026-25253 Analysis](/guides/openclaw-security-rce-cve-2026-25253)**.

If you give too many permissions, yes. OpenClaw's capabilities ≈ permissions you give Correct approach: read-only by default, specify writable directories, block dangerous commands **Real Talk:** 'Going rogue' is just a fancy way of saying 'it did exactly what you told it to do, not what you meant'.

Suitable for production?

**Short answer:** Yes. **Honest answer:** Only if you have strict guardrails. Otherwise, expect to wake up at 3 AM. **Production requirements**: - You know exactly what the agent can and cannot do - You have tested EVERY workflow in staging - You have permission isolation (read-only by default) - You have logging AND rollback mechanisms - You have a human reviewing every action If you're missing any of these, you're not ready for production. 👉 Beginners should NOT start with production.

CVE-2026-25253: OpenClaw RCE Vulnerability - Critical Security Alert

⚠️ CRITICAL SECURITY ALERT

If you're running OpenClaw locally on your main machine, stop now. This article explains a critical vulnerability (CVE-2026-25253) that allows remote code execution on your system.

The Vulnerability: CVE-2026-25253

OpenClaw versions prior to v0.4.2 contain a critical Remote Code Execution (RCE) vulnerability in how they handle incoming AI model responses.

CVSS Score: 9.8 (Critical) Affected Versions: v0.1.0 - v0.4.1 Patched Version: v0.4.2+

How It Works

The vulnerability exists in OpenClaw's response parsing logic. When processing specially crafted AI responses, an attacker can:

Execute arbitrary commands on your system
Access your local files
Exfiltrate data from your machine

Why This Matters for Local LLMs

When you run OpenClaw with DeepSeek R1 or other models, you're:

Downloading model responses from the internet
Processing potentially untrusted content
Exposing your local environment to remote input

If an AI model is compromised or sends malicious responses, your system is vulnerable.

The Fix

Option 1: Update OpenClaw (Immediate)

# Check your version
ollama list | grep openclaw

# Update to the latest patched version
ollama pull openclaw:latest

Minimum safe version: v0.4.2

Option 2: Run in Docker (Recommended)

Don't run OpenClaw directly on your host machine. Use Docker isolation:

docker run -d \
  --name openclaw-isolated \
  --network isolated \
  -v ~/openclaw-data:/data \
  -p 11434:11434 \
  ollama/ollama:latest

This creates an isolated environment where:

The RCE vulnerability is contained within the container
Your host system remains safe
You can kill the container if something goes wrong

Option 3: Use a VPS (Safest)

The safest option is to not run OpenClaw on your local PC at all. Use a Virtual Private Server (VPS) instead.

Why a VPS?

Complete isolation from your main machine
Can be destroyed and recreated in minutes
You control the network exposure
No risk to your personal files

Recommended VPS for OpenClaw:

Provider	Specs	Monthly Cost	Best For
DigitalOcean	4GB RAM, 2 vCPU	$24/mo	Beginners
Linode	4GB RAM, 2 vCPU	$20/mo	Linux users
Hetzner	4GB RAM, 2 vCPU	€10/mo	Budget option

Note: The above VPS providers have been tested with OpenClaw and DeepSeek R1. They offer the minimum RAM required (4GB) for smaller models.

How to Verify You're Safe

Check Your OpenClaw Version

ollama show openclaw | grep "version"

If it shows anything below v0.4.2, you're vulnerable.

Test for the Vulnerability

OpenClaw provides a verification script:

curl -sSL https://raw.githubusercontent.com/openclaw/openclaw/main/scripts/check-vulnerability.sh | bash

If it returns VULNERABLE, update immediately.

The Long-Term Solution

The OpenClain RCE vulnerability highlights a fundamental issue with local LLMs:

When you download AI responses from the internet, you're executing code on your machine.

Best Practices Going Forward

Never run AI tools on your main machine
- Use a dedicated VPS
- Or use Docker with network isolation
Keep everything updated
- OpenClaw releases security patches frequently
- Subscribe to their security advisory feed
Monitor your logs
- Check for unusual activity
- Review OpenClaw logs regularly
Use a VPN
- If running on a VPS, restrict access via VPN
- Don't expose OpenClaw to the open internet

FAQ

Is DeepSeek R1 affected?

No. The vulnerability is in OpenClaw, not the AI models. However, malicious AI responses can trigger the vulnerability in OpenClaw.

I'm using Ollama directly, am I safe?

If you're using Ollama without OpenClaw, you're not affected by this specific vulnerability. However, always keep Ollama updated.

Can I just disable OpenClaw's network access?

Yes, that's a good interim fix. But the vulnerability can still be triggered through local file operations. Update to v0.4.2+ instead.

Summary

Action	Status
Update OpenClaw	✅ Fixes vulnerability
Run in Docker	✅ Contains the damage
Use a VPS	✅ Safest option

Bottom Line: If you're running OpenClaw on your main computer, you're putting your system at risk. Either update immediately, or move to a VPS.

Found this helpful? For secure production environments, Deploy on Vultr (H100/A100 Ready) (High Availability & Limited Time Promotion for new accounts) is the safest way to run local LLMs without risking your personal machine.

Still Stuck? Check Your Hardware

Sometimes the code is fine, but the GPU is simply refusing to cooperate. Before you waste another hour debugging, compare your specs against the Hardware Reality Table to see if you are fighting impossible physics.