1-to-N avatar operation is a method in which an operator can simultaneously control multiple avatars. Each time the operator switches to a different avatar, they must cognitively process and understand that avatar’s current situation (mental context switching). As the number of avatars increases and more information is fed to the operator from each one, the time required for mental context switching also increases. This leads to greater cognitive overload for the operator and, consequently, a higher risk of misidentification. Attackers can exploit such misidentification to carry out social engineering attacks against the operator without infiltrating the avatar operating system itself. This paper investigates the parameters associated with mental context switching in 1-to-N avatar operation environments and discusses an experimental design to explore the feasibility of such attacks.