Configuration changes on network devices are a routine task for network operators; however, misconfigurations sometimes cause significant network downtime. Configuration repair aims to safely automate this task by inferring new configuration parameters that satisfy operators' high-level network change intents. Despite its benefit, existing repair tools could introduce unexpected forwarding path changes not described by the change intents (i.e., side effects). These side effects hinder their real-world deployment, as such path changes occur without the operators' awareness. We propose ISR, a new augmentative framework for repair tools to prevent undesired side effects in satisfying network change intents. The key idea is iterative specification refinement: ISR (1) identifies side effects in configurations after repair, (2) generates minimal repair specifications to prevent them, and (3) feeds these specifications back into the next repair. This iterative process guides repair tools to find configuration parameters that satisfy change intents without introducing undesired side effects. We evaluate the effectiveness and scalability of ISR on real network topologies. We first demonstrate that ISR successfully guides three repair tools (SMT/Simulation/LLM-based) to generate configurations that satisfy change intents without introducing undesired side effects in OSPF and BGP networks. Second, the scalability evaluation shows that ISR completes a refinement iteration within seconds for varying numbers of side effects on the topologies with up to 200 nodes.