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After collecting a drawer full of Raspberry Pis over the years (we all have that drawer, right?), I decided it was time to put them to work. Here are five security projects that actually solve real problems, complete with implementation guides and lessons learned.

How It Works

⚠️ Warning: These Raspberry Pi security projects are for educational purposes. Deploy only in authorized environments with proper network permissions and security controls.

flowchart TB
    subgraph threatactors["Threat Actors"]
        TA1[External Attackers]
        TA2[Insider Threats]
        TA3[Supply Chain]
    end
    subgraph attackvectors["Attack Vectors"]
        AV1[Network]
        AV2[Application]
        AV3[Physical]
    end
    subgraph defenses["Defenses"]
        D1[Prevention]
        D2[Detection]
        D3[Response]
    end

    TA1 & TA2 & TA3 --> AV1 & AV2 & AV3
    AV1 & AV2 & AV3 --> D1
    D1 -->|Bypass| D2
    D2 --> D3

    classDef greenNode fill:#4caf50
    classDef orangeNode fill:#ff9800
    classDef redNode fill:#f44336
    class D1 greenNode
    class D2 orangeNode
    class D3 redNode

Requirements

The scripts demonstrated in this post use Python libraries including OpenCV (opencv-python for computer vision), python-nmap (network scanning), and paramiko (SSH automation). Install via: pip install opencv-python python-nmap paramiko

Why Raspberry Pi for Security?

Before diving into projects, let's address the elephant in the room: Why use a $35 computer for security when enterprise solutions exist?

I've found several compelling reasons through my own experiments:

  1. Low Power Consumption: Running 24/7 costs pennies
  2. Silent Operation: No fans = no noise in your home
  3. Versatility: From network monitoring to physical security
  4. Learning Platform: Mistakes are cheap and educational
  5. Real Solutions: These aren't toys – they solve actual problems (at least in my experience)

Project 1: The Network Sentinel – DNS Sinkhole & Monitor

Problem Solved: Ads, tracking, and malicious domains accessing your network

For enterprise-grade DNS security, see my guide on implementing DNS-over-HTTPS to encrypt DNS traffic and prevent eavesdropping.

The Backstory: Devices on our network were hitting 400+ tracking domains per hour. Per. Hour. That's when I knew we needed a bouncer at the network door.

Hardware: Raspberry Pi 4 (2GB), microSD card, Ethernet cable

Implementation

# Install Pi-hole
curl -sSL [https://install.pi-hole.net](https://install.pi-hole.net) | bash

# Add custom blocklists for security
cd /etc/pihole
sudo wget [https://raw.githubusercontent.com/RPiList/specials/master/Blocklists/malware.txt](https://raw.githubusercontent.com/RPiList/specials/master/Blocklists/malware.txt)
sudo wget [https://raw.githubusercontent.com/RPiList/specials/master/Blocklists/ransomware.txt](https://raw.githubusercontent.com/RPiList/specials/master/Blocklists/ransomware.txt)
sudo wget [https://raw.githubusercontent.com/RPiList/specials/master/Blocklists/phishing.txt](https://raw.githubusercontent.com/RPiList/specials/master/Blocklists/phishing.txt)

# Update gravity database
pihole -g

Enhancements I Added

The DNS monitoring script uses Python's tailer library to follow Pi-hole's query log in real-time. It watches for suspicious patterns like excessive queries to unknown domains, connections to known malicious IPs from threat feeds, and domain generation algorithm (DGA) patterns using regex matching. When detected, it sends notifications via Pushover or email.

Results: Blocking 30-40% of DNS queries (mostly ads/tracking), caught 3 malware callbacks in 6 months, kids' devices are significantly faster.

Project 2: The Silent Guardian – Motion Detection Security Camera

Problem Solved: Package theft, wanting to monitor specific areas without cloud dependencies

Hardware: Raspberry Pi Zero W, Pi Camera v2, PIR motion sensor, 3D printed case

Implementation

Using OpenCV's background subtraction and contour detection, the motion security system analyzes frames from the Pi Camera, filtering false positives through frame differencing and minimum area thresholds. Detected motion triggers GPIO outputs (siren, lights) and saves annotated frames with bounding boxes.

Results: Caught multiple package delivery attempts, identified a raccoon problem (AI classifier initially misidentified it as a person), zero false alerts after tuning.

Project 3: The Honeypot – Early Warning System

Problem Solved: Detecting network intrusion attempts before they reach real systems

Honeypot data integrates well with threat intelligence dashboards to map attacker TTPs to MITRE ATT&CK.

Hardware: Raspberry Pi 3B+, Ethernet connection

Implementation

The SSH honeypot listens on ports 22, 2222, and 8022 using Python's socket library with multi-threaded handling. It logs connection attempts, captures login credentials (stored hashed), and records basic interaction patterns to identify scanning behavior vs targeted attacks.

Results: Detected 3 targeted scans of my network, identified compromised IoT device attempting lateral movement, fascinating data on bot behavior.

Project 4: The Vault Guardian – Hardware Security Key Backup

Problem Solved: Secure backup for 2FA recovery codes and emergency access

Hardware: Raspberry Pi Zero, OLED display, button, encrypted SD card

Implementation

The secure vault combines AES-256 encryption (Python cryptography library) with physical access control. A tactile button triggers the OLED display to show time-based recovery codes (TOTP), ensuring secrets remain encrypted at rest and only accessible via physical presence.

Results: Peace of mind knowing recovery codes are offline but accessible, survived a YubiKey failure gracefully, spouse approved the "break glass" simplicity.

Project 5: The Compliance Scanner – Automated Security Auditing

Problem Solved: Keeping track of security posture across multiple devices

Scale this approach with open-source vulnerability management for enterprise-grade scanning across 200+ assets.

Hardware: Raspberry Pi 4 (4GB), good network connection

Implementation

Automated daily scans use nmap for service discovery and paramiko for SSH-based configuration checks. The scanner verifies settings like SSH key-only authentication, disabled root login, firewall status, and automatic updates. Results generate markdown reports with findings categorized by risk level (critical/high/medium/low).

Results: Found 2 IoT devices with default passwords, discovered forgotten test VM with open services, maintains security baseline visibility.

Lessons Learned

After implementing these projects, here are my key takeaways:

1. Start Simple, Iterate Often

My first Pi-hole setup was basic. Now it has custom blocklists, monitoring scripts, and integration with my SIEM. Evolution is normal.

2. Physical Security Matters

That expensive Arlo camera? My Pi Zero setup catches more relevant events because I positioned it better and tuned it myself. Your mileage may vary depending on your specific setup and environment.

3. False Positives Will Happen

My honeypot initially alerted on my own port scans. My motion detector thought shadows were intruders. Tuning is crucial.

4. Power and Network Reliability

Invest in good power supplies and consider PoE HATs. Nothing worse than your security system going down during a storm.

5. Documentation Is Security

Every project has a README with recovery procedures. When something breaks at 2 AM, you'll thank yourself.

Cost Analysis

Total investment for all five projects:

  • Raspberry Pis: ~$200
  • Accessories (cases, cards, sensors): ~$100
  • Time invested: ~40 hours
  • Knowledge gained: Priceless

Compare that to:

  • Enterprise DNS filter: $500+/year
  • Cloud security camera: $10+/month
  • SIEM subscription: $100+/month
  • Vulnerability scanner: $2000+/year

What's Next?

I'm currently experimenting with some ambitious ideas (though they're still in early testing):

  1. AI-Powered Threat Detection: Using Coral TPU for real-time network traffic analysis (see AI edge computing for deployment patterns)
  2. Mesh Security Network: Multiple Pis creating a distributed security sensor network
  3. Incident Response Bot: Automated playbook execution via Discord commands

For advanced security monitoring, explore eBPF security monitoring to add kernel-level threat detection to your homelab.

Your Turn

These projects solve my specific problems, but the beauty of Raspberry Pi is customization. Maybe you need:

  • A secure password manager display
  • Network usage monitor for kids' devices
  • Automated backup verification system
  • Physical security for a specific door/window

The key is identifying a real problem and building a focused solution.

Resources

  • Hardware: CanaKit for reliable Pi bundles
  • Cases: Check Thingiverse for security-specific Pi cases
  • Community: r/raspberry_pi and r/homelab are goldmines
  • My Scripts: [GitHub - Coming Soon](sanitizing for public release)

Remember: The best security system is one that actually gets used. These Raspberry Pi projects work because they're maintainable, understandable, and solve real problems.

What security problem will you solve with your next Pi?

Have questions about any of these projects? Found a cool use for your Pi? Let me know! I'm always looking for the next practical security project.

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