mlsanityData to 14 Oct 2026

Beyond Single-Use Tokens: Durable Authorization State for Replay-Resistant LLM Agent Actions

arXiv 2608.01710 ↗First posted 3 Aug 2026cs.AIcited by 7

On the map: LLM agents and tool use → Agent threats, guardrails and governance

Abstract (arXiv)

Tool-using large language model agents frequently replan, retry failed operations, delegate tasks, and resume after crashes. These behaviors can cause one user authorization to be requested and executed multiple times under freshly issued token identifiers, even when each individual token is single-use. We call this failure semantic replay: exceeding the execution budget of a token-independent authorization instance rather than merely reusing an old token identifier. We show that identifier-local token consumption cannot prevent fresh reissuance unless the issuer retains monotonic durable state over the authorized action, confirmation event, and remaining execution budget. We introduce CapLease, an authorization-consumption layer that follows proposal- and authority-level defenses, binds an authenticated user confirmation to a canonical action, and enforces transactional Issue-Prepare-Commit transitions. Across LLM-agent replanning, retry, delegation, concurrency, confirmation-replay, and crash-recovery scenarios, identifier-local tokens permit fresh semantic reissuance, whereas CapLease and an equally stateful Server Ledger prevent duplicate admission and, with an idempotent sink, duplicate external effects. Our results identify durable authorization state, rather than token representation alone, as the systems requirement for replay-resistant agent execution.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 10 of its 25 references that are in the map. First posted on arXiv 3 Aug 2026.

Builds on

10 of 25 references.

Closest ancestors · 8

Same direction, newest first

  1. 2026Context-to-Execution Integrity for LLM Agents7 Jul
  2. 2026AIRGuard: Guarding Agent Actions with Runtime Authority Control27 May
  3. 2026The Granularity Mismatch in Agent Security: Argument-Level Provenance Solves Enforcement and Isolates the LLM Reasoning Bottleneck11 May
  4. 2026SUDP: Secret-Use Delegation Protocol for Agentic Systems27 Apr
  5. 2025LlamaFirewall: An open source guardrail system for building secure AI agents6 May
  6. 2025Defeating Prompt Injections by Design24 Mar
  7. 2025MELON: Provable Defense Against Indirect Prompt Injection Attacks in AI Agents7 Feb
  8. 2024Agent Security Bench (ASB): Formalizing and Benchmarking Attacks and Defenses in LLM-based Agents3 Oct

Other references · 2

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  2. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,182

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 7.

7 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2026ACRFence: Preventing Semantic Rollback Attacks in Agent Checkpoint-Restore
  2. 2026Agent Memory Is a Surface for Endogenous Authorization Laundering
  3. 2026ContractBench: Can LLM Agents Preserve Observation Contracts?
  4. 2026From Approval to Execution: Reconstruction-Aware Repair Analysis for LLM-Agent Software
  5. 2026Temporary Authority, Permanent Effects: Commit-Time Authorization for LLM Agents
  6. 2026When Memory Becomes Authority: Benchmarking Authority Collapse at the Memory Consolidation Boundary
  7. 2026Persistent Billable State: Denial-of-Wallet Attacks and Defenses in Tool-Calling LLM Agents
  8. 2026Capability Gates Are Not Authorization: Confused-Deputy Failures in LLM Agent Frameworks