We will explore two kinds of adversarial attacks: 1) injecting a few adversarial cells into an existing grid running a pretrained model; and 2) perturbing the global state of all cells on a grid. For the first type of adversarial attacks we train a new CA model that, when placed in an environment running one of the original models described in the previous articles, is able to hijack the behavior of the collective mix of adversarial and non-adversarial CA. The second type of adversarial attacks interact with previously trained growing CA models by perturbing the states within cells.