Silverfort describes declared-intent control model for AI agent purpose-to-permission mismatch detection

Silverfort published a blog detailing a control pattern that normalizes an agent's natural-language instruction into a reviewable declared purpose, compares it against tool bindings/permissions/live actions, and triggers human approval or revocation on divergence (e.g., from prompt injection or hijacked identity).

Introduces 'intent-to-access' comparison as a distinct exposure category for agent governance programs, complementing existing NHI/identity security tooling, though this reads as a capability description rather than a discrete new product SKU.

Governance teams building agent inventories should consider declared purpose as a required field and treat mismatch as a reviewable exposure.