Introduction

Most network visibility tools are built for enterprise environments — switches, firewalls, SIEMs.

But what happens at the edge?

What happens in the air?

This project started with a simple question:

Can a low-cost device like an ESP32 be used to perform meaningful Wi-Fi reconnaissance and basic security analysis?

The answer turned into something much more interesting.


The Idea

The goal was not to build another Wi-Fi scanner.

The goal was to build a portable reconnaissance and risk-scoring tool for wireless environments.

Something that could:

  • Passively observe Wi-Fi activity
  • Identify potential risks
  • Provide meaningful insights — not just raw data

This led to the creation of ESP32 IoT Scout — a lightweight, embedded tool focused on visibility and detection at the edge. oai_citation:0‡LinkedIn


Why ESP32?

The ESP32 is often seen as a hobbyist device.

In reality, it’s:

  • Cheap
  • Power efficient
  • Equipped with Wi-Fi capabilities
  • Flexible enough for real-world experimentation

It’s widely used in IoT because it can handle networking, storage, and hardware interfaces in a compact form factor. oai_citation:1‡GitHub

This makes it a perfect candidate for security experimentation at the edge.


What the Project Does

At its core, ESP32 IoT Scout focuses on passive Wi-Fi analysis.

Key capabilities include:

  • Wi-Fi scanning (SSID, BSSID, RSSI, channel)
  • Vendor identification via OUI
  • Basic risk scoring
  • Detection patterns (e.g., anomalies, suspicious behavior)
  • Channel analysis and environment awareness

Unlike traditional tools, the focus is not just visibility — but contextual understanding.


Architecture Overview

The device operates as a passive listener.

It does not connect to networks.

It observes.

High-level flow:

  1. Scan Wi-Fi environment
  2. Collect metadata (SSID, MAC, signal, channel)
  3. Enrich data (OUI/vendor lookup)
  4. Apply scoring and detection logic
  5. Present results locally (OLED / interface)

This approach aligns with how modern reconnaissance tools work:

  • Passive first
  • Low footprint
  • Context-driven

Security Perspective

Most people associate ESP32 security projects with offensive techniques like Evil Twin attacks or deauthentication.

Those exist — and are well documented. oai_citation:2‡GitHub

But this project takes a different direction:

Detection instead of attack

It focuses on:

  • Understanding wireless environments
  • Identifying anomalies
  • Building awareness

This is closer to defensive security engineering than penetration testing.


Challenges

Building this was not trivial.

1. Limited resources

  • Memory constraints
  • Processing limits
  • Need for efficient data structures

2. Real-time analysis

  • Continuous scanning
  • Avoid blocking operations
  • Balance accuracy vs performance

3. Signal interpretation

  • RSSI is not reliable alone
  • Channel hopping complexity
  • Noise vs real signals

4. Data enrichment

  • OUI lookup optimization
  • Storage constraints (LittleFS)

What Makes It Interesting

This project sits at the intersection of:

  • Networking
  • Security
  • Embedded systems

But more importantly:

It brings security visibility to places where traditional tools don’t exist

Think about:

  • Retail stores
  • Warehouses
  • Offices without full monitoring
  • Temporary environments

Future Direction

There are several directions this can evolve into:

  • Device fingerprinting
  • Client behavior analysis
  • Detection of rogue patterns (e.g., AirSnitch-like behavior)
  • Integration with backend systems
  • Historical tracking and anomaly detection

Long term, this could evolve into a distributed edge sensing system.


Final Thoughts

This project is not about replacing enterprise tools.

It’s about exploring a different layer of visibility.

The wireless edge is still largely unobserved.

And sometimes, all it takes is a small device to start seeing it.


Project

You can find the full project here:

https://github.com/LucaBiancorosso/ESP32_IoT_Scout