Delinea, Cyera integrate to link identity access with data exposure risk

SAN FRANCISCO—Delinea and Cyera announced a product integration that connects privileged identity access with sensitive data exposure, aiming to help security teams better identify and prioritize high-risk access paths.

The integration links Delinea’s identity security platform with Cyera’s data security posture management (DSPM) technology, correlating identities with the data they can access and applying risk context based on data sensitivity.

As organizations manage a growing number of human, machine and AI-driven identities, understanding which accounts have access to critical data has become increasingly complex. The companies said connecting identity and data context is intended to give security teams clearer visibility into potential risk.

“Organizations cannot afford to manage access risk in one tool and data risk in another and hope someone connects the dots,” said Chris Kelly, president of Delinea. “Security teams need better context to prioritize risk and govern access with confidence.”

Integration brings data context into identity risk scoring

Through the integration, Cyera identifies and classifies sensitive data across cloud and on-premises environments, then shares that context with Delinea via API (Application Programming Interface). The system correlates identities with the data they can access and factors that information into risk scoring.

Accounts with access to higher-value or more sensitive data are prioritized, enabling security teams to focus remediation efforts and enforce least-privilege access controls based on potential impact.

The companies said this approach is designed to shift identity security from a volume-based model - focused on large numbers of alerts or entitlements - to a risk-based model that prioritizes exposure tied to critical assets.

Focus on prioritization and visibility

Delinea and Cyera outlined several intended benefits of the integration, including helping teams identify the most critical exposures, reduce time spent investigating lower-risk alerts, and bring identity and data risk into a single view.

By combining identity and data context, the integration aims to provide a more complete picture of exposure, particularly as artificial intelligence (AI)-driven systems increase the speed and scale at which identities interact with sensitive information.