As part of the research on biometric features of handwriting, a specialized web application was developed to capture data about touch events on smartphones touchscreen. The application was implemented using HTML5 and JavaScript with the Canvas element to create an interactive input area. The study involved 40 participants, each of whom entered the same random three-character handwritten passphrase 25 times. The study focuses on random forgeries only. The biometric data of handwriting was recorded on a Redmi Note 9 Pro device (rate of touch sampling at 60 Hz), with the additional ability to capture biometric features such as: coordinates, timestamps, touch contact area and touchscreen pressure sensitivity. Biometric data of random signatures are stored in Excel document format, which are further processed by tools of the Python programming language. For comparison, the article presents tables of results and graphs demonstrating the similarity of biometric features of handwriting with the public available database of signatures SVC2004. The developed web application can be used by scientific researchers, preferably with citation to this work.