ACLE-MCP is presented, an invocation-scoped architecture that couples delegated authorization, workload appraisal, and resource-side execution admission that indicates that invocation-time binding between call authority and current workload state is a practical complement to OAuth-protected remote tool use.
Abstract
Remote Model Context Protocol (MCP) services enable large language model agents to invoke external tools, but OAuth authorization alone does not ensure that a later tool call is executed by the provider-side workload that the relying party intended to trust. An endpoint may remain authorized even after execution shifts to a substituted workload, relies on stale appraisal state, reuses authority transferred from another sender, or traverses an undeclared downstream component. We call this problem the post-authorization execution trust gap. We present ACLE-MCP, an invocation-scoped architecture that couples delegated authorization, workload appraisal, and resource-side execution admission. For protected calls, ACLE-MCP issues a short-lived, sender-constrained capability lease that binds the expected workload, freshness requirement, operation, object and parameter bounds, downstream constraints, and receipt obligations. A provider-side Execution Gate consumes the lease immediately before protected tool logic begins. We implement a runnable prototype with Keycloak/OIDC validation, an MCP Python SDK server, and an optional vTPM quote-verification backend. Controlled security experiments and an agent tool-use extension show that weaker authorization or connect-time attestation modes leave distinct post-authorization attacks open, whereas full ACLE-MCP blocks all evaluated attack families while preserving all benign tasks. In the locally simulated agent extension, the complete design increases request-level pooled p95 latency on normal allowed calls by 25.7% relative to OAuth-only. These results indicate that invocation-time binding between call authority and current workload state is a practical complement to OAuth-protected remote tool use.
The results show that TraceGrant provides a unified governance layer that connects trusted user intent, runtime evidence, concrete tool execution, and verified task completion.
Bohao Liao, Jing-Chao Wang, Qi-Peng Song et al.· 1 citation
Background Zero-Trust access control for cloud APIs is well established, but hybrid High-Performance Computing (HPC)-to-Quantum Processing Unit (QPU) workflows have a lifecycle existing mechanisms were not built for: a job queues for minutes to days, is dispatched, executes, and only then releases results, while identi...
Fouad Ailabouni, Jesús-Ángel Román-Gallego· Open Research Europe· 0 citations
A tool-using model can follow a malicious instruction even when its credentials are valid. We study whether task-scoped authorization contains the resulting tool execution. Our paired-replay testbed samples a model request once and submits the same action, resource, and arguments to broad bearer, scoped JWT, sender-con...
The results show that plan-first execution combined with label-preserving persistence can substantially strengthen persistent LLM agents, while revealing an important security-utility tradeoff introduced by strict integrity enforcement.
This work introduces ToolFence, which compiles a typed authorization blueprint before execution, enforces it through a deterministic monitor, and when the blueprint is incomplete asks a judge to grant new capabilities rather than adjudicate each concrete call, improving runtime efficiency.
Yan-Jie Li, Xiang-Yu He, Xue-Long Dai et al.· 0 citations
LLM agents translate natural-language context, which may include attacker-controlled text, into privileged tool calls, so authorization must remain effective even when an agent is prompt-injected or adversarially steered. The Model Context Protocol (MCP) has become a widely adopted interface for this boundary, yet its...