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Sharing high-quality research data specifically for reuse in future work helps the scientific community progress by enabling researchers to build upon existing work and explore new research questions without duplicating data collection efforts. Because current discussions about research artifacts in Computer Security focus on reproducibility and availability of source code, the reusability of data is unclear. We examine data sharing practices in Computer Security and Measurement to provide resources and recommendations for sharing reusable data. Our study covers five years (2019–2023) and seven conferences in Computer Security and Measurement, identifying 948 papers that create a dataset as one of their contributions. We analyze the 265 accessible datasets, evaluating their under-standability and level of reuse. Our findings reveal inconsistent practices in data sharing structure and documentation, causing some datasets to not be shared effectively. Additionally, reuse of datasets is low, especially in fields where the nature of the data does not lend itself to reuse. Based on our findings, we offer data-driven recommendations and resources for improving data sharing practices in our community. Furthermore, we encourage authors to be intentional about their data sharing goals and align their sharing strategies with those goals.