Electric vehicles (EVs) play an important role in smart grids. They can be operated in two modes of operations which are grid-to-vehicle (G2V) and vehicle-to-grid (V2G). Recently, EVs are involved in peak-shaving processes where their vehicle-to-grid operation mode can be used to supply power to the grid in times of peak load. On the other hand, the frequency of extreme events and man-made attacks (cyber and physical attacks) is in a dramatic increased in recent years. These events have severe impacts on power systems whether they cause long outage times or major equipment destruction. The first step against these attacks is to understand how they are built and their impact on the power system. This paper investigates the impact of the false data injection (FDI) attacks on EV chargers and distributed generation resources (DGs) of the active distribution networks (ADN). FDI attacks focus on the operation of the distribution system optimal power flow (DSOPF) analysis to increase the losses in the system and accordingly, increase the costs. For the analysis of the FDI attack impacts, the IEEE-38 bus balanced power distribution system is considered, with distributed energy resources (DERs) along the system represented by bidirectional interactive EVs (BIEV), dispatchable DG units, and wind power plants. A 24-hour AC DSOPF is performed on General Algebraic Modeling System (GAMS) software, where the changes in the status of a set of EV chargers and voltage profile are resulted along with an increase in the injected power from DERs which consequently lead to an increase in system losses and DSOPF cost.