Cyera AI Security Platform

Assigns risk scores to discovered data based on sensitivity, access exposure, and configuration, then continuously monitors access patterns and policy compliance to surface the highest-risk data stores for action.

Discovers and classifies sensitive data (PII, PHI, PCI data, IP) across cloud object storage, relational and NoSQL databases, data lakes, and SaaS platforms using content inspection and ML classification.

Continuously monitors data access patterns and flags anomalous or unauthorized access in real time.

Identifies sensitive data in locations outside authorized data stores, development databases containing production PII, unprotected S3 prefixes, forgotten data lake partitions.

Maps effective permissions to sensitive data stores across cloud IAM, database roles, and SaaS permissions, identifies over-privileged access and dormant entitlements.

Connects to cloud object storage, data warehouses, on-premises databases, and SaaS platforms for discovery and classification, with coverage depth varying by product.

Traces how sensitive data moves between storage locations, services, and users, surfaces unexpected cross-region transfers, shadow copies, and retention policy violations.

Verifies that sensitive data is stored and processed only in approved geographic regions, mapping data locations to applicable residency requirements (GDPR EEA, Australian Privacy Act, data sovereignty laws).

Automatically remediates discovered violations, revoking over-permissioned access, moving misplaced data to compliant storage, encrypting unprotected sensitive files.

Maps effective permissions to sensitive data stores, identifying every identity with access, at what level, and whether that access has been used recently.

Consumes sensitivity labels from data classification tools (Purview, Varonis, Nightfall) to apply access governance policies based on data sensitivity tier.

Discovers and enforces data policies for content stored in or transiting through cloud applications and storage, extending DLP coverage to SaaS environments without endpoint agents.

Applies sensitivity labels to data automatically based on content analysis and context without requiring users to manually classify documents before policy enforcement.

Detects and controls sensitive data entered into generative AI tools, applying block, redact, or warn actions before data leaves the organization.

Correlates DLP policy violations with user behavioral context, distinguishing routine data movement from anomalous exfiltration patterns associated with insider threat or account compromise.

Monitors and enforces data movement policies on endpoints, blocking or logging USB transfers, clipboard operations, print jobs, and screen captures of content matching classification policies.