Aurva continuously discovers and classifies sensitive data such as personally identifiable information (PII), financial data, and regulated data across databases, data warehouses, object storage, and SaaS platforms. Classification is enriched with contextual metadata and natural language processing for higher accuracy.
Unlike traditional DSPM tools that focus only on static data locations, Aurva links sensitive data to actual access paths and identities. This identity-aware approach helps security teams identify over-privileged access, misconfigurations, and exposure risks that truly matter.
Aurva also prioritizes data risks using real posture signals such as sensitivity, exposure level, access sprawl, and external sharing. This allows teams to focus remediation efforts on high-impact data assets rather than low-risk findings.
