With the rapid development of computer science and the long-term development of software services, many software companies routinely collect and analyze telemetry data from users to improve user experience. The same is true for us. In order to improve the performance of a static code analysis tool, it is constructive to provide tool developers with comprehensibility and feedback on corresponding operations. However, the collection of telemetry data can enhance the user experience, it also brings apparent risks to the user’s privacy. First we provided background knowledge and regulations on privacy protection. With the support of the methodology, we gradually applied a top-down privacy analysis method STPA-Priv to assess the privacy risk of the telemetry function. STPA-Priv’s application shows its flexibility and practicality in socio-technological scenarios. Then, we designed a telemetry data system for the feedback channel of a static code analysis tool. We discussed and compared different encryption schemes during this process and finally determined a hybrid encryption scheme of RSA and AES. After that, we proposed an abstract code representation, an abstract syntax tree, which protects the privacy and guarantees the intellectual property rights of the source code. Finally, we completed and tested the prototype of the telemetry channel in practice. Experimental results showed that the feedback channel designed for static code analysis tools guaranteed the utility of data based on protecting user data security.