On February 28th, shortly after the Russian invasion of Ukraine, Twitter announced the expansion of its labelling policy for “Russia state-affiliated media”, in order to address disinformation in favour of the Russian government. While this ‘soft’ approach does not include the removal of content, it entails issues for the freedom of expression and information. This article addresses the consequences of this labelling policy for the range and impact of accounts labelled “Russia state-affiliated media” during the Ukrainian war. Using an iterative detection method, a total of 90 accounts of both media outlets and individual journalists with this label were identified. The analysis of these accounts’ information and timeline, as well as the comparison of the impact of their tweets before and after February 28th with an ARIMA model, has revealed that this policy, despite its limited scope, lead to a significant reduction in the impact of the sampled tweets. These results provide empirical evidence to guide critical reflection on this content moderation policy.