Self-Adaptive Systems (SAS) are becoming more evident in our lives. By definition, these systems are supposed to adapt to changes in their context without human interference. It is essential that they are trusted to autonomously perform critical tasks in changing environmental conditions. That makes assuring their safety a vital task, and because of their complexity, a challenging one. My goal is to identify potential safety vulnerabilities in safety requirements of SAS at design time. This would provide the system architect with a tool which facilitates the early detection of failures in the system and subsequently reduce the time and effort of the development.