How to Track the People Tracking YOU

David Bombal explores digital privacy and surveillance detection in his content, particularly focusing on a tool called “Chasing Your Tail”—an open-source project developed by Matt Edmondson and showcased at Black Hat 2025. This device uses a Raspberry Pi equipped with GPS and network sniffing tools (like Kismet) to detect if someone is following you by scanning Wi-Fi, Bluetooth, and even vehicle tire sensor signals.

The system works by identifying consistent appearances of the same MAC addresses or device signatures across multiple locations. Once an “ignore list” is created for known devices (like your own), any unfamiliar, recurring devices may indicate surveillance. The tool can then map both your route and the follower’s movement patterns, flipping the script on trackers.

It was originally designed to avoid surprise visits from a boss at a military warehouse but has since evolved into a serious privacy and security solution used in high-risk environments like hospitals and by federal agents. The project is 100% free and open source, emphasizing accessibility and community-driven innovation.

Technical Components and Setup

The “Chasing Your Tail” device leverages:

Raspberry Pi as the core hardware
GPS module for location tracking
Kismet for wireless network detection
Python-based scripts for data analysis and visualization

It scans for Wi-Fi probe requests, Bluetooth signals, and other wireless emissions from nearby devices—even when they’re not connected to any network. Despite MAC address randomization (used by modern phones like iPhones), the tool analyzes behavioral patterns and frequency of appearances to identify potential tracking.

Building it costs under $100, and full instructions, including code, are available on GitHub. David Bombal highlights how AI helped refine the codebase, making it more robust and user-friendly.

Real-World Applications and Impact

The tool has been deployed in real-life scenarios:

Hospital staff in high-threat areas use it for situational awareness.
Search and rescue teams utilize it to detect signals in disaster zones.
Private individuals concerned about stalking or digital surveillance benefit from its early-warning capabilities.

Even special operations units have expressed interest, proving that simple, open-source tools can complement advanced surveillance systems.

David emphasizes that this isn’t just about personal security—it raises broader questions about digital privacy, consent, and the Internet of Things (IoT). As more devices emit wireless signals, the line between convenience and vulnerability blurs.

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