A dataset inventory is a structured record of the data sources used to train a model, including where the data came from, what license or other rights apply, and any restrictions on reuse, retention, or distribution. It turns training data from an opaque collection into something that can be reviewed and audited.
In cyber security, dataset inventories support governance, incident response, and legal defensibility. They help teams prove that training data was acquired legitimately, identify sensitive or restricted content, and quickly trace exposure if a dataset contains personal data, trade secrets, or copyrighted material. Attackers may try to poison training sets, hide unlicensed material, or smuggle harmful examples into public corpora; a good inventory makes those risks easier to detect. Defenders use inventories with provenance logs and access controls to verify model lineage, enforce opt-outs, and answer auditors or regulators when they ask what data shaped a system.