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Wireless Zero Trust Detection & Response Lab

License: MIT Python 3.8+ Python Security Lab Check

Defensive wireless security lab that detects suspicious 802.11 Wi-Fi activity using Python, Scapy, configurable detection rules, and Zero Trust response logic. The lab safely simulates wireless events in memory and logs SOC-style alerts without transmitting attack traffic.

Built to connect enterprise wireless networking experience with blue-team detection engineering.

Why I Built This

I built this project to bridge enterprise wireless networking and cybersecurity detection engineering. The goal was to show how suspicious Wi-Fi behavior can be detected, scored, logged, and mapped to a Zero Trust response workflow in a safe lab environment.

What It Detects

Detection Purpose
Deauthentication flood Identify possible wireless disruption behavior
Unknown wireless device Flag untrusted MAC addresses
Evil twin AP Detect suspicious SSID/BSSID mismatch behavior
Beacon flood Identify abnormal beacon activity
Probe requests Log suspicious discovery behavior
Trust-score changes Reduce trust based on suspicious activity
Simulated isolation Log guarded containment decisions

How It Works

  1. Simulated packets or offline PCAP packets are sent to the detector.
  2. Detection rules are loaded from config/detection_rules.json.
  3. Trusted devices and SSID/BSSID expectations are loaded from config/trusted_devices.json.
  4. Alerts are written to logs/alerts.log and logs/alerts.jsonl.
  5. Suspicious trusted devices lose trust score.
  6. If risk and trust thresholds allow it, simulated containment is logged.

Architecture

flowchart LR
    A[Simulated Scapy Packets / Optional PCAP] --> B[Attack Detector]
    B --> C[Detection Rules]
    C --> D[SOC-style Alerts]
    C --> E[Zero Trust Trust Engine]
    E --> F[Trust Score Update]
    F --> G{Risk + Trust Threshold Met?}
    G -->|Yes| H[Guarded Simulated Isolation]
    G -->|No| I[Log and Continue]
    H --> J[logs/alerts.log]
    D --> J
    J --> K[logs/alerts.jsonl]
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Real-World Mapping

In a production wireless environment, this workflow could map to:

  • Wireless LAN Controller telemetry
  • Cisco ISE / NAC policy decisions
  • Rogue AP and client behavior monitoring
  • SIEM alert ingestion
  • SOAR response approval
  • Identity-aware quarantine workflows

What Makes This Different

This project is intentionally built as a defensive blue-team lab, not a wireless attack toolkit. Instead of focusing on exploitation, it shows how wireless signals can flow through detection rules, risk scoring, SOC-style logging, trust-score reduction, and guarded simulated response. It is small by design: configurable enough to demonstrate real security thinking, but simple enough to read, test, and explain.

Run The Lab

pip install -r requirements.txt
python3 run_lab.py

View alerts:

cat logs/alerts.log
cat logs/alerts.jsonl

Optional PCAP Analysis

python3 src/pcap_analyzer.py --pcap path/to/wireless_capture.pcap

Try the small included sample:

python3 src/pcap_analyzer.py --pcap sample-data/wireless_lab_sample.pcap

The analyzer also handles non-wireless PCAPs and reports when no 802.11 frames are present. Only analyze captures you are authorized to use.

Tests

pip install -r requirements-dev.txt
pytest

Configuration

Detection thresholds, severities, and cooldowns live in:

config/detection_rules.json

Trusted devices, trusted SSID/BSSID expectations, trust penalties, and response safety controls live in:

config/trusted_devices.json

Resume Relevance

This project demonstrates hands-on experience with:

  • Wireless security detection concepts
  • Python and Scapy-based packet simulation
  • Zero Trust trust scoring
  • SOC-style alert logging
  • Detection rules and threshold tuning
  • Network security response workflow design

Notes

This is a lab project, not a production wireless IDS. MAC addresses can be spoofed, thresholds need tuning, and real deployments should combine this kind of logic with controller telemetry, NAC identity, SIEM correlation, and RF context.

Safety

This project is for educational and defensive use only. Test only on systems and networks you own or have permission to assess.

About

Wireless Zero Trust Detection & Response lab using Python and Scapy, with deauth flood, unknown MAC, Evil Twin, beacon flood detection, trust scoring, JSON alerts, and CI.

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