Unverified50% confidenceConceptExact time
Agents need to access data as the user but should not obtain permissions beyond the task scope, which requires fine-grained scope design and an auditable delegated authorization model.
1
Sources
50%
Confidence
Long-term
Relevance
10/22/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedApplied to desktop agents, this means the agent should not receive all of the user's own credentials, but should use a separate, scope-restricted account or token.76% similarUnverifiedFor agents capable of spawning sub-agents or accessing external repositories, mandatory pre-execution constraints and hard checkpoints should be established rather than relying on post-hoc audits.76% similarUnverifiedCommon means of mitigating the permission risks brought by Agents autonomously opening accounts include using short-lived credentials, limiting scope by task, requiring manual secondary confirmation for sensitive operations, and recording complete invocation audit logs.75% similarUnverifiedThe user-consent-centric authorization model has exposed its limitations in the context of the proliferation of AI Agents, MCP servers, and enterprise-grade applications, as it cannot support the centralized management, policy enforcement, and audit trail capabilities required for enterprise-level authorization.75% similarUnverifiedThe key differences between permission models for Agents and models for humans include: the caller has no interactive login interface, and the key is the identity; an Agent may represent multiple principals and require fine-grained delegation; permission decisions must be machine-readable, cacheable, and low-latency.74% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1086011API
curl https://kongchang.com/api/v1/knowledge/claims/1086011MCP
get_claim(id=1086011)