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Introduction:
When a suspicious IP appears in your logs, the traditional workflow involves manually checking VirusTotal, GreyNoise, Shodan, AbuseIPDB, and several other services—each with its own login, API key, rate limits, and browser tab. Incident responders waste 15 minutes or more per indicator, often hitting rate limits or timing out. IONSEC’s Clawhub (OpenClaw) solves this by consolidating 14+ threat intelligence services into a single command, handling automatic rate limiting, response caching, and bulk processing—returning comprehensive results in under 30 seconds.
Learning Objectives:
- Automate threat intelligence lookups using a unified CLI tool that queries VirusTotal, GreyNoise, Shodan, Spur.us, and Validin simultaneously.
- Implement rate limiting and response caching to avoid API bans and reduce redundant queries during incident response.
- Build custom DFIR scripts that integrate Clawhub with SIEM alerts, log analysis pipelines, and automated playbooks.
You Should Know:
1. One-Command Threat Intelligence Aggregation
The core value of Clawhub is turning a fragmented, multi-tab investigation into a single terminal command. Instead of manually visiting each threat intel platform, you run:
Linux/macOS - after installing OpenClaw clawhub analyze ip 185.130.5.253 Windows (PowerShell with clawhub.exe) .\clawhub.exe analyze ip 185.130.5.253 --output json
What this does: The tool simultaneously queries VirusTotal (detection ratio), GreyNoise (malicious/C2 classification), Shodan (open ports/services), Spur.us (VPN/Tor exit node detection), and Validin (passive DNS history). Results are aggregated into a single readable output.
Step‑by‑step installation and usage:
- Clone the repository: `git clone https://github.com/IONSec/OpenClaw.git` (or use the Clawhub link)
2. Install dependencies: `pip install -r requirements.txt` (Python 3.8+ required) - Set up API keys (optional for free tier, but recommended):
export VIRUSTOTAL_API_KEY="your_key" export GREYNOISE_API_KEY="your_key" export SHODAN_API_KEY="your_key"
- Run a basic IP check: `clawhub analyze ip
`
5. For bulk analysis from a log file:
clawhub batch analyze --input suspicious_ips.txt --output results.json --threads 10
- Automatic Rate Limiting & Caching for Production DFIR
API rate limits are the bane of incident responders—AbuseIPDB limits free tiers to 1000 queries per day, Shodan times out frequently. Clawhub implements a token-bucket rate limiter and Redis-backed cache to prevent hitting limits and to reuse results for identical queries within a configurable TTL.
Step‑by‑step configuration:
1. Enable caching (default SQLite, optional Redis):
clawhub config set cache.enabled true clawhub config set cache.ttl 3600 1 hour
2. Set rate limits per service (respects each API’s policies):
clawhub config set ratelimit.virustotal 4 4 requests per minute clawhub config set ratelimit.greynoise 60 60 per minute for paid tier
3. Test with high concurrency to verify queuing:
for i in {1..100}; do clawhub analyze ip 8.8.8.8 --async & done
4. View cache stats: `clawhub cache stats`
- Clear cache before a new incident: `clawhub cache clear`
Windows equivalent:
Using PowerShell environment variables $env:CLAWHUB_CACHE_ENABLED="true" .\clawhub.exe config set ratelimit.shodan 30
3. Bulk Processing and SIEM Integration
Real-world DFIR involves hundreds or thousands of IPs from firewall logs, IDS alerts, or Zeek conn logs. Clawhub’s batch mode processes lists efficiently with parallel threads and incremental output.
Step‑by‑step bulk workflow:
- Extract unique IPs from your SIEM (example with Splunk or Elastic):
Export from Splunk to CSV, then extract IPs cut -d',' -f3 splunk_export.csv | sort -u > ips_to_check.txt
2. Run batch analysis with resume capability:
clawhub batch analyze --input ips_to_check.txt --output incident_2026-04-11.json \ --resume --threads 20 --rate-limit global=100
3. Filter results for malicious indicators:
cat incident_2026-04-11.json | jq '.[] | select(.virustotal.detections > 5 or .greynoise.classification == "malicious")'
4. Generate a CSV report for stakeholders:
clawhub batch report --input incident_2026-04-11.json --format csv --output report.csv
5. Pipe directly from a live log stream:
tail -f /var/log/auth.log | grep "Failed password" | awk '{print $NF}' | clawhub batch analyze --stdin
4. Extending Clawhub with Custom Threat Intel Sources
The tool is open-source (OpenClaw) and allows adding your own API modules—ideal for internal threat feeds, commercial TI platforms, or custom ML models.
Step‑by‑step custom integration:
1. Locate the modules directory: `cd /opt/OpenClaw/modules/`
- Create a new Python module `custom_feed.py` following the base class:
from clawhub.base import ThreatIntelModule class CustomFeed(ThreatIntelModule): def query(self, indicator): Call your internal API response = requests.get(f"https://internal-ti.company/api/ip/{indicator}", headers={"X-API-Key": self.api_key}) return {"custom_score": response.json()["risk"], "source": "Internal"}
3. Register the module in `config.yaml`:
modules:
- name: custom_feed
enabled: true
api_key: ${CUSTOM_FEED_KEY}
4. Test the integration: `clawhub analyze ip 10.0.0.1 –module custom_feed`
5. Rebuild the container if using Docker: `docker build -t clawhub-custom .`
5. Leveraging the Free Tier and On-Prem Deployment
IONSEC provides a free tier covering essential services (VirusTotal limited, GreyNoise community, Shodan free). For air-gapped or high-privacy environments, you can deploy Clawhub entirely on-prem with your own API keys and local caching.
Step‑by‑step on-prem deployment:
1. Pull the Docker image: `docker pull ionsec/clawhub:latest`
2. Run with persistent cache volume:
docker run -d --name clawhub \ -v /data/clawhub_cache:/cache \ -e VIRUSTOTAL_API_KEY=$VT_KEY \ -e GREYNOISE_API_KEY=$GN_KEY \ -p 8080:8080 ionsec/clawhub:latest
3. Enable the REST API mode for integration with SOAR platforms:
clawhub server --host 0.0.0.0 --port 8080
4. Query via curl from any security tool:
curl -X POST http://localhost:8080/api/v1/analyze \
-H "Content-Type: application/json" \
-d '{"indicator": "185.130.5.253", "type": "ip"}'
5. For Kubernetes deployments, use the provided Helm chart:
helm repo add ionsec https://ionsec.io/charts helm install clawhub ionsec/clawhub --set cache.redis.enabled=true
6. Mitigation Playbook Integration: From Detection to Blocking
Once Clawhub identifies a malicious IP, the next step is automated mitigation. Combine the tool with firewalls, EDR, or cloud security groups.
Step‑by‑step automated blocking:
- Create a wrapper script that runs Clawhub and triggers actions:
!/bin/bash IP=$1 RESULT=$(clawhub analyze ip $IP --format json) MALICIOUS=$(echo $RESULT | jq '.greynoise.classification == "malicious"') if [ "$MALICIOUS" == "true" ]; then Block via iptables (Linux) sudo iptables -A INPUT -s $IP -j DROP Block via Windows Firewall netsh advfirewall firewall add rule name="Block_$IP" dir=in remoteip=$IP action=block Log to SIEM logger "Blocked malicious IP $IP based on Clawhub detection" fi
2. For cloud environments (AWS Security Group):
aws ec2 revoke-security-group-ingress --group-id sg-123456 --protocol tcp --port 22 --cidr $IP/32
3. Integrate with CrowdStrike or SentinelOne via API:
curl -X POST https://api.crowdstrike.com/policies/blocklist \
-H "Authorization: Bearer $CS_TOKEN" \
-d "{\"indicator\": \"$IP\", \"action\": \"block\"}"
4. Schedule periodic scans of recent logs:
Cron job every hour 0 /usr/local/bin/clawhub batch analyze --input /var/log/failed_auth_ips.txt --output /reports/hourly_$(date +\%Y\%m\%d_\%H).json
7. Windows-Specific Usage and PowerShell Automation
For Windows-based DFIR teams, Clawhub runs natively via Python or compiled executable, with full PowerShell integration.
Step‑by‑step Windows setup:
- Download the Windows executable from GitHub releases or use `pip install openclaw`
2. Add to PATH: `setx PATH “%PATH%;C:\tools\clawhub”`
- Create a PowerShell advanced function for incident responders:
function Invoke-ThreatIntel { param([bash]$IP) $result = clawhub analyze ip $IP --format json | ConvertFrom-Json if ($result.virustotal.detections -gt 5) { Write-Warning "Malicious IP detected: $IP" Add to Windows Defender Firewall New-NetFirewallRule -DisplayName "DFIR_Block_$IP" -Direction Inbound -RemoteAddress $IP -Action Block } return $result } - Integrate with Windows Event Logs (failed RDP attacks):
Get-WinEvent -LogName Security | Where-Object {$<em>.Id -eq 4625} | ForEach-Object { $ip = $</em>.Properties[bash].Value Invoke-ThreatIntel -IP $ip }
5. Schedule with Task Scheduler for continuous monitoring:
<!-- Register a scheduled task --> schtasks /create /tn "Clawhub_Analyze" /tr "powershell -File C:\scripts\analyze_events.ps1" /sc hourly
What Undercode Say:
- Automation is the force multiplier: Clawhub reduces IP investigation from 15 minutes to 30 seconds, allowing DFIR teams to focus on remediation rather than manual data gathering. The open-source model ensures transparency and customizability.
- Rate limiting and caching are non-negotiable for production use: Many security tools ignore API constraints, leading to bans or incomplete data. Clawhub’s built-in token bucket and Redis cache make it enterprise-ready, especially for bulk processing during active breaches.
- Integration with existing workflows is key: The ability to pipe logs, export to JSON, and trigger firewall blocks turns a CLI tool into a core component of a SOAR platform. Windows and Linux support plus a REST API means it fits anywhere.
Prediction:
As threat actors increasingly use fast-flux networks and ephemeral C2 infrastructure, manual indicator lookups will become completely obsolete. Tools like Clawhub that aggregate multiple TI sources with automated rate handling will evolve into real-time, streaming analysis engines—ingesting Zeek logs, Suricata alerts, and cloud flow logs directly, and feeding back into zero-trust enforcement points. Within 18 months, we expect most mid-to-large SOCs to replace their fragmented browser‑based TI workflows with unified CLI or API-driven aggregators, and open-source projects like OpenClaw will set the standard for transparency and community-driven threat intel modules.
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Reported By: Nirhalfon Dfir – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
