Wi-Fi Offensive and Defensive Security Toolkit
Having dedicated the past year and a half to my final year project, I’ve successfully developed a powerful and hands-on Wi-Fi Offensive and Defensive Security Toolkit leveraging the capabilities of Python and Scapy on a Raspberry Pi. This project goes beyond theoretical concepts, providing a practical platform to simulate real-world wireless attacks and implement effective defense mechanisms.
Designed as both an educational resource and a robust security auditing tool, this toolkit offers invaluable hands-on experience with the offensive and defensive intricacies of Wi-Fi networks. Whether you’re a fellow penetration tester, a cybersecurity student looking to bridge the gap between theory and practice, or a hobbyist eager to explore the depths of wireless security, this project offers a unique and practical learning opportunity.
Introduction
In today’s world, wireless networks remain a primary target for attackers due to inherent vulnerabilities in the Wi-Fi protocol stack. Traditional tools often address either attack or defense — rarely both. This project bridges that gap.
The Wi-Fi Offensive and Defensive Security Toolkit is a Raspberry Pi-based solution designed to scan, attack, detect, and defend Wi-Fi networks in real time. Built using Python and Scapy, it provides hands-on insight into wireless attacks and mitigation strategies through a modular, menu-driven interface.
1. System Overview
The toolkit is built around four core modes:
- Offensive Mode: Includes deauthentication, beacon flooding, WPA2 handshake capture, MITM, and DNS spoofing.
- Defensive Mode: Detects deauth attacks, rogue APs, ARP spoofing, and triggers alerts.
- War Driving Mode: Logs surrounding APs and performs security audits based on encryption type.
- Automated Mode: Executes chained attacks autonomously — from scanning to key cracking.
All modes are powered by Scapy for raw packet manipulation and Hostapd for fake AP creation. The toolkit also includes a real-time intrusion dashboard hosted on Flask, accessible via browser.
2. Key Features
🗡️ Offensive Capabilities
- Deauthentication Attack
- Beacon Flooding / Fake APs
- WPA2 Handshake Capture & Cracking
- ARP Spoofing & DNS Spoofing
- SSL Stripping & Credential Harvesting
🛡️ Defensive Capabilities
- Rogue AP Detection
- Deauth Detection
- ARP Spoofing Alerts
- DNS Spoofing Alerts
🔎 Recon & Audit
- War Driving Module
- AP Security Score Classification (Open → WPA2-802.11w)
- GPS Tagging & Signal Strength Filtering
📊 Real-Time Dashboard
- MongoDB-Backed Dashboard for Defense Toggle and Traffic Analysis
- Live Monitoring of Wi-Fi Events
- Control Defensive Mechanisms in Real Time
3. Testing Methodologies
3.1 Unit Testing
Each module was tested in isolation:
- Packet Injection Testing: Verified proper crafting of deauth and beacon packets.
- Handshake Capture: Ensured .cap files were compatible with Aircrack-ng.
- Fake AP Broadcasts: Confirmed visibility on client devices.
- Dashboard Logging: Checked accurate and real-time updates.
3.2 Integration Testing
All modules were integrated and tested together:
- Automated Mode Execution: Confirmed smooth transitions across attack stages.
- Defense Mode: Detected all injected attacks in near real-time.
- Recon + Audit Workflow: Seamlessly logged APs and calculated scores.
3.3 Performance Testing
Measured under varying conditions:
- Handshake Capture Time: 3–7 minutes average (weak passphrases).
- Deauth Success Rate: 80–90% depending on AP proximity.
- Dashboard Latency: Alerts showed within 3–5 seconds.
- Resource Use: CPU/memory remained under 70% on Raspberry Pi 4.
3.4 Security Testing
Real-world attacks were simulated:
- MITM + Credential Capture
- DNS Spoofing with Fake Google Login
- Resilience Testing with WPA2-802.11w Enabled APs
4. Contributions and Innovations
🔐 Protocol-Level Discovery
Attempted to block deauthentication attacks via software filtering, but discovered that 802.11w (Management Frame Protection) was the most reliable solution. The toolkit thus recommends hardened APs using hostapd with WPA2 + 802.11w.
🧰 Integrated Attack-Defense Framework
Unlike other tools, this combines both offensive and defensive modules. Ideal for penetration testers, researchers, and students alike.
🛰️ Real-Time Intrusion Dashboard
Built-in dashboard shows:
- Active attacks
- Spoofed frames
- Detected rogue APs
- Deauth logs and timestamps
🧬 Custom Packet Engineering
Every attack is custom-coded in Scapy, unlike tools like aircrack-ng that abstract low-level behavior. This gives fine-grained control for educational purposes.
🔁 Fully Automated Mode
Automatically loops through:
- Scan for APs
- Select weakest one
- Launch deauth
- Capture handshake
- Crack password
- Log and move to next
5. Results and Analysis
5.1 Handshake Capture & Cracking
- 85% capture rate across test APs
- 3–7 mins average cracking time (weak passwords)
- Strong WPA2 passwords resisted dictionary attacks
5.2 Deauthentication Attacks
- 90% success in client disconnection
- Best results within 10 meters
- 802.11w APs mitigated most attacks
5.3 MITM & ARP Spoofing
- 100% success on non-802.1X networks
- Unencrypted traffic yielded credentials
- Detected within 10 seconds
5.4 DNS Spoofing
- Successful redirection post-ARP spoofing
- Harvested credentials via fake Google login
- Worked only on non-HSTS and HTTP sites
5.5 Rogue AP Detection
- 100% detection via SSID/MAC mismatch
- 85% DoS success on fake APs
- Dashboard flagged excessive beacons in <5s
5.6 Recon & AP Audit
- Logged 50+ APs in 500m radius
- Classification accuracy: 95%
- Open / WEP / Weak WPA2 / WPA2+802.11w
5.7 Defense Mode
- 98% detection of deauth & ARP spoofing
- Alerts triggered within 3–5 seconds
- WPA2-802.11w APs resisted 90% of deauths
5.8 Automated Mode
- 80% success rate in chained attacks
- 4–6 minutes/AP on average
- Skipped failed attempts to optimize workflow
Conclusion
The Wi-Fi Offensive and Defensive Toolkit is a unique, hands-on solution for learning, testing, and securing Wi-Fi networks. It doesn’t just execute attacks — it teaches how they work and how to mitigate them.
Whether you’re a cybersecurity student, a red teamer, or a wireless researcher, this project provides:
- A modular learning environment
- Practical defense tools
- Real-world attack simulation
- Protocol-level insights
With growing threats in wireless environments, understanding both sides of the security spectrum is no longer optional — it’s essential.
Next Steps
- Install script for easy deployment
- Add support for WPA3 and Evil Twin detection
- Leave feedback or contribute to future versions!
Built with Scapy, Python, Raspberry Pi, and a passion for wireless security.