About

This site focuses on the security and privacy analysis of RF signaling systems from an adversarial ("black hat") perspective. The emphasis is on practical exploitability: what can realistically be observed, decoded, inferred, or manipulated using commercially available software-defined radios (SDRs), custom signal processing techniques, and modern AI-assisted analysis.

The capabilities available to both researchers and attackers have changed dramatically in recent years. Affordable wideband SDRs, open-source software, machine learning, and inexpensive GPU computing have significantly lowered the barrier to reverse engineering and analyzing many wireless protocols that were once considered difficult to study. As a result, assumptions about the security or obscurity of proprietary RF systems often deserve to be revisited.

My current interests include smart utility metering systems and other low-power wireless telemetry technologies, although many of the methods used are broadly applicable to proprietary RF protocols, industrial telemetry, and IoT devices.

This work is conducted partly as a personal research effort and partly through selective consulting engagements. My technical background includes many years developing RF signal processing algorithms and techniques as an engineer at a large engineering firm, providing a foundation for applying today's SDRs and AI-based analysis tools to practical wireless security problems.

The goal is not to facilitate attacks, but to better understand the real-world capabilities of potential adversaries so that wireless systems can be designed and deployed with more realistic security assumptions.

Questions, comments, or discussions are always welcome at contact@waveformsecurity.com.