Background: Testing and validation of the semantic correctness of patches provided by tools for Automated Program Repairs (APR) has received a lot of attention. Yet, the eventual acceptance or rejection of suggested patches for real world projects by humans patch reviewers has received a limited attention. Objective: To address this issue, we plan to investigate whether (possibly incorrect) security patches suggested by APR tools are recognized by human reviewers. We also want to investigate whether knowing that a patch was produced by an allegedly specialized tool does change the decision of human reviewers. Method: In the first phase, using a balanced design, we propose to human reviewers a combination of patches proposed by APR tools for different vulnerabilities and ask reviewers to adopt or reject the proposed patches. In the second phase, we tell participants that some of the proposed patches were generated by security specialized tools (even if the tool was actually a `normal' APR tool) and measure whether the human reviewers would change their decision to adopt or reject a patch. Limitations: The experiment will be conducted in an academic setting, and to maintain power, it will focus on a limited sample of popular APR tools and popular vulnerability types.