mlsanityData to 7 Oct 2026

AID-Guard: Stateful Authorization for Delegated Agent Effects

arXiv 2608.21159 ↗First posted 21 Aug 2026cs.CR cs.AIcited by 5

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Abstract (arXiv)

Tool-using AI agents turn delegated tasks into provider effects, yet authorization often ends at admission while provider state, delivery, retry, and recovery evolve. A request may change before commit, or response loss may cause a replacement to create a second effect from one approval. We present AID-Guard, a stateful authorization-to-effect closure protocol. It revalidates the approved request and provider state at commit, retains one reservation under ambiguity, and permits release or one successor only after a terminal result or certified no effect with a delivery fence. For supported provider contracts, one reservation yields at most one effect across retry and recovery. To our knowledge, it is the first evaluated agent-authorization protocol to unify these controls in one lifecycle. We implement a Python/SQLite prototype. In a declared loopback MCP domain, 13 live mutations caused no unauthorized provider effects, three concurrent histories were linearizable, and evidence bundles supported public verification and replay. All 210 Stripe provider-contract trials matched predeclared outcomes. Across Stripe and Resend, 40 terminalize-successor schedules, 30 overlapping races, and 10 crash-recovery schedules completed without duplicate effects. Under complete proposer compromise, AID-Guard blocked 44/44 attacks and admitted 44/44 matched legitimate proposals. Its strict exact-manifest profile reduced benign utility by 35.4 to 43.8 percentage points; a typed frontier recovered 9-10 completions without observed unsafe effects. A composition study blocked 20/20 post-admission lifecycle attacks and preserved 8/8 valid or exact-retry executions. The results support authorization-to-effect binding under the evaluated effect-path inventory, provider contracts, and failure schedules.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 16 of its 35 references that are in the map. First posted on arXiv 21 Aug 2026.

Builds on

16 of 35 references.

References · 16

  1. 2025Defeating Prompt Injections by Designcited by 256
  2. 2024Defending Against Indirect Prompt Injection Attacks With Spotlightingcited by 233
  3. 2024IsolateGPT: An Execution Isolation Architecture for LLM-Based Agentic Systemscited by 118
  4. 2025Securing AI Agents with Information-Flow Controlcited by 108
  5. 2025ACE: A Security Architecture for LLM-Integrated App Systemscited by 52
  6. 2026Taming Various Privilege Escalation in LLM-Based Agent Systems: A Mandatory Access Control Frameworkcited by 50
  7. 2025SAGA: A Security Architecture for Governing AI Agentic Systemscited by 45
  8. 2026Cordon: Semantic Transactions for Tool-Using LLM Agentscited by 19
  9. 2026Temporary Authority, Permanent Effects: Commit-Time Authorization for LLM Agentscited by 17
  10. 2026Aligning Provenance with Authorization: A Dual-Graph Defense for LLM Agentscited by 12
  11. 2026AIP: Agent Identity Protocol for Verifiable Delegation Across MCP and A2Acited by 10
  12. 2026Agent libOS: A Runtime Substrate for Capability-Controlled Self-Evolving LLM Agentscited by 8
4 more
  1. 2026Context-to-Execution Integrity for LLM Agentscited by 7
  2. 2026Bounded Agents: Delegation Security for Multi-Agent AI Systemscited by 6
  3. 2026Beyond Single-Use Tokens: Durable Authorization State for Replay-Resistant LLM Agent Actionscited by 5
  4. 2026Beyond OAuth: Task-Scoped Authorization for AI Agents via Natural Language Slicescited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 5.

5 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2026Stateful Governance for Concurrent Agentic Systems
  2. 2026HALO: Heterogeneous Admission through Localized Obligations for Safe Agentic Execution
  3. 2026LeaseGuard: Incumbent-Preserving Admission Control for Privileged LLM Agents
  4. 2026Trust Is Not a Score: Runtime Assurance Contracts for High-Risk AI Agents
  5. 2026Self-Healing Harness for Runtime Oversight of Agent Self-Modification
  6. 2026Boundary-State Control for Tool-Using Language-Model Agents: Commit-Time Consistency under State Drift
  7. 2026Runtime Authorization for Resources Acquired by AI Agents
  8. 2026Authorization Closure Graph: Minimal Repair for LLM Agents with Evolving User Instructions