In false data injection (FDI) attacks, the attackers can impose security impacts by injecting false data into meter measurements to affect the security-constraint economic dispatch, which develops the dispatch for the end of a dispatch interval. Thus, the existing security analysis methods basically assess the attack impact based on a snapshot of system condition at the interval end, at which the dispatch target is achieved. Such analysis falls into a static analytical framework (SAF). However, with the increasing share of intermittent resources, the system is suffering short-term fluctuations, which may increase the variability and render security weak points inside of a dispatch interval. Smart attackers can judiciously exploit these weak points to impose large impacts on the Intra-Interval operational security. Such cyber risk may be underestimated under the SAF adopted by existing methods. To address such risk, a dynamic analytical framework is proposed in this article for analyzing the Intra-Interval operational security impacts of potential FDI attacks by considering the system variability in the dispatch interval. Simulations are performed based on the historical wind data on the IEEE 118-bus system, which verify the effectiveness of the proposed approach and highlight the risk of such issues in power systems with significant wind penetration.