Building a Chat-Driven Shodan Automation Workflow (OpenClaw Skill)

liuweitao

I’ve been experimenting with turning Shodan into a conversational research assistant using OpenClaw.

Instead of manually crafting filters and queries every time, I let the AI handle:

• Query building
• Result interpretation
• Trend analysis
• API quota monitoring
• Safe research workflows

I wrapped Shodan into a Skill for OpenClaw here:

👉 https://github.com/liuweitao/shodan-skill

After installing the skill and setting your API key, you can start interacting with Shodan in a completely different way.

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1️⃣ What Can It Actually Do?

Me:
What can you do with this Shodan Skill?

OpenClaw:
With Shodan Pro access, I can act as a full internet exposure research assistant.

Here are the main capabilities:

🌍 Asset Discovery

• Search exposed services worldwide
• Filter by country, product, organization
• Query specific CVEs
• Fingerprint via favicon hash

Example:
search --query "product:apache country:SG"

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📊 Trend & Macro Analysis

• Compare global usage of technologies
• Count exposed ICS systems by country
• Analyze SSL certificate distribution

Example:
count --facets product

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🔬 Deep Host Inspection

• Full host profile (ports, services, metadata)
• DNS intelligence
• Historical exposure data

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📡 Monitoring & Scanning

• Real-time stream monitoring
• Asset alerts
• On-demand re-scan (API credit based)

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🧠 Built-in Knowledge Base

• Filter lookup
• Shodan data field explanations

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2️⃣ API Key Status Check (Practical Example)

One thing I liked is that it can introspect the API limits automatically.

Me:
Check my API key status and tell me what features are unavailable.

OpenClaw:
API Status Report:

• Plan: EDU
• Status: Unlocked

Credits:

Resource	Remaining	Status
Query Credits	199,799 / 200,000	Plenty
Scan Credits	65,536 / 65,536	Full
Monitored IPs	0 / 131,072	Available

Restrictions:

• No Firehose full stream access
• No bulk raw data export

This is surprisingly convenient — no need to manually check dashboard pages.

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3️⃣ Large-Scale Exposure Research (Safety Discussion)

I also tested how it would handle a hypothetical large-scale exposure study workflow.

For example:

• Collecting asset lists
• Performing slow, rate-limited verification
• Logging progress
• Handling API interruptions
• Implementing checkpoint resume logic

The assistant automatically suggested:

• Low concurrency
• Randomized delays
• Incremental saving
• Crash recovery logic
• Periodic reporting

What I found interesting wasn’t the scanning itself —
it was the workflow orchestration ability.

It can:

• Detect partial API fetch failures
• Restart jobs safely
• Implement retry logic
• Kill background tasks cleanly
• Verify that no residual processes remain

Example:

Me:
Stop everything and delete all related files.

OpenClaw:
✔ Process terminated
✔ Scheduled tasks removed
✔ Data directory deleted
✔ No active background jobs remaining

For people running automation-heavy research on small VPS instances (like many of us here), this type of orchestration layer is actually useful.

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4️⃣ Why This Is Interesting for LET Users

Many of us here:

• Run small VPS nodes
• Experiment with automation
• Do infrastructure research
• Monitor exposed services
• Build lightweight tooling

What this setup gives you is:

• A natural-language interface to Shodan
• Automated research pipelines
• API credit awareness
• Controlled execution strategies
• Clean teardown capability

It turns Shodan from a search engine into something closer to a programmable recon assistant.

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5️⃣ Important Note

This setup is intended for:

• Research
• Defensive exposure analysis
• Academic usage
• Monitoring your own infrastructure

Not for active exploitation or abusive scanning.

Always respect:

• Laws
• Hosting provider policies
• Responsible disclosure practices

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If anyone here is interested in testing or improving the skill, feedback is welcome:

👉 https://github.com/liuweitao/shodan-skill

Would love to hear how others on LowEndTalk would use something like this.