Zero Trust for data

  • Zero Trust for Data: When Sensitive Is a Label, Not a Control

    Zero Trust for Data: When Sensitive Is a Label, Not a Control

    Daniel Linstedt

    Zero Trust for data reframes “sensitive” from a label into an executive expectation that access is bounded, continuously verified, and provable. The core liability emerges when permissions, copies, and usage pathways expand faster than the enterprise can constrain or evidence them. Access sprawl becomes a rational outcome of delivery pressure, reuse incentives, and reluctance to…

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  • Zero Trust for Data When Sensitive Is Only a Label

    Zero Trust for Data When Sensitive Is Only a Label

    Daniel Linstedt

    Many enterprises treat sensitive data as a label and assume policy implies protection. Zero Trust for data reframes this as an executive expectation that access must be bounded, continuously verified, and provable. The central failure mode is access sprawl, where entitlements, exceptions, copies, and derivatives expand faster than accountability can keep up. As analytics and…

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  • Zero Trust for Data: When Sensitive Is a Label, Not a Control

    ByDaniel Linstedt

    Zero Trust for data reframes “sensitive” from a label into an executive expectation that access is bounded, continuously verified, and provable. The core liability emerges when permissions, copies, and usage pathways expand faster than the enterprise can constrain or evidence them. Access sprawl becomes a rational outcome of delivery pressure, reuse incentives, and reluctance to remove entitlements once granted. Analytics and AI intensify the problem by multiplying derivatives and consumption paths that outlive their original justification. The article contrasts a technology upgrade posture with a system redesign posture and explains where incentives and authority collide. It closes with executive questions that surface whether governance can be enforced and demonstrated, not merely documented.

  • Zero Trust for Data When Sensitive Is Only a Label

    ByDaniel Linstedt

    Many enterprises treat sensitive data as a label and assume policy implies protection. Zero Trust for data reframes this as an executive expectation that access must be bounded, continuously verified, and provable. The central failure mode is access sprawl, where entitlements, exceptions, copies, and derivatives expand faster than accountability can keep up. As analytics and AI multiply consumption paths, proof obligations shift from documentation to evidence that controls worked at the point of use. The result is decision friction that surfaces in funding gates, entitlement reviews, and governance escalations rather than in tooling debates.