The study of information-sharing cascades has been a constant endeavor since the emergence of social networks. Internet memes which mostly consist of catchphrases, viral images, or small videos shared over the social network are notorious for attracting the users’ attention and spreading through the web in a fast fashion. Misinformation propagators latch their message to a meme to maximize the influence and spreading of the false news. As a result, the diffusion of misleading content has become a force to be reckoned with in the field of information warfare, as foreign actors seek to change opinions, manipulate ideologies, and create conflicts. In this study, we analyze the rapid dissemination of misinformation, aka, misinformation cascades, focusing on cascade temporal behavior and multi-cascade influence relationships. Twitter data used in this study contains only information associated with the Russian Internet Agency (IRA) and the Iranian Cyber Army (ICA). Our study focuses on analyzing temporal patterns of information dynamics created by these foreign actors for the sole purpose of spreading misinformation. We explore dividing temporal cascades into phases, where each phase differs from the previous regarding the number and characteristics of the information bursts. For this preliminary study, we are focusing on the #Trump and #USA hashtags used by the ICA. By studying the dynamics behind each phase, the forces behind the transition from one phase to another, and the influence relationships between cascades and their phases, we expect to shed some light on the timely subject of how to identify and protect society from information manipulation campaigns.