As a natural interaction approach, handwriting acts as an essential role in human–computer interaction. In order to achieve ubiquitous and reliable applications, a handwriting recognition system should be easy to use without any intrusion and robust to environment changes, which cannot be satisfied in most of existing approaches. In this article, we present <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RFPad</i> , a device-free handwriting recognition system with a tag square consisting of four low-cost passive radio frequency identification (RFID) tags. With such an ingenious tag square, we transform the flat surface into a handwriting platform, and build a geometry-based theoretical model between the finger positions and the tags' phase variations so that the finger trajectory can be accurately tracked and handwriting can be recognized with the phases segmented from continuous signals. We implement a prototype of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RFPad</i> using commercial off-the-shelf RFID devices and conduct extensive experiments to evaluate its performance. Experiment results show that our <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RFPad</i> can track finger movement with an average error of 1 cm and achieve average recognition accuracy of 94.08 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> for all 26 handwriting capital letters.