ACRFence: Preventing Semantic Rollback Attacks in Agent Checkpoint-Restore
On the map: LLM agents and tool use → Agent threats, guardrails and governance
Abstract (arXiv)
LLM agent frameworks increasingly offer checkpoint-restore for error recovery and exploration, advising developers to make external tool calls safe to retry. This advice assumes that a retried call will be identical to the original, an assumption that holds for traditional programs but fails for LLM agents, which re-synthesize subtly different requests after restore. Servers treat these re-generated requests as new, enabling duplicate payments, unauthorized reuse of consumed credentials, and other irreversible side effects; we term these semantic rollback attacks. We identify two attack classes, Action Replay and Authority Resurrection, validate them in a proof of concept experiment, and confirm that the problem has been independently acknowledged by framework maintainers. We propose ACRFence, a framework-agnostic mitigation that records irreversible tool effects and enforces replay-or-fork semantics upon restoration
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 10 of its 42 references that are in the map. First posted on arXiv 21 Mar 2026.
Builds on
10 of 42 references.
Closest ancestors · 4
Same direction, newest first
- 2025AgentSight: System-Level Observability for AI Agents Using eBPF2 Aug
- 2025Progent: Securing AI Agents with Privilege Control16 Apr
- 2025AgentSpec: Customizable Runtime Enforcement for Safe and Reliable LLM Agents24 Mar
- 2025Commercial LLM Agents Are Already Vulnerable to Simple Yet Dangerous Attacks12 Feb
Other references · 6
- 2024OpenHands: An Open Platform for AI Software Developers as Generalist Agentscited by 956
- 2024Non-Determinism of "Deterministic" LLM Settingscited by 84
- 2025Get Experience from Practice: LLM Agents with Record & Replaycited by 22
- 2026Replayable Financial Agents: A Determinism-Faithfulness Assurance Harness for Tool-Using LLM Agentscited by 7
- 2026Fork, Explore, Commit: OS Primitives for Agentic Explorationcited by 5
- 2026Beyond Reproducibility: Token Probabilities Expose Large Language Model Nondeterminismcited by 3
Built on by
Citing papers per year: 2026: 9.
9 papers.
- 2026From Agent Traces to Trust: A Survey of Evidence Tracing and Execution Provenance in LLM Agentscited by 29
- 2026Resume Means Resume: A Machine-Checked Conformance Contract for Checkpoint, Interrupt, and Resume Semantics in Workflow Persistence Layerscited by 2
- 2026Safe to Resume? Breaking Execution Continuity of Agent Execution via Rollbackcited by 2
- 2026Sandlock: Confining AI Agent Code with Unprivileged Linux Primitivescited by 1
- 2026Governed Capability Evolution: Lifecycle-Time Compatibility Checking and Rollback for AI-Component-Based Systems, with a Proof-of-Concept Evaluation on Embodied Agentscited by 0
- 2026REVISE: Validity-Guided Recovery for Online Revisions in Agent Workflowscited by 0
- 2026When Tool Calls Succeed but Workflows Fail: Anomalies at the Agent-Tool Boundarycited by 0
- 2026Planarian: Managing Agent State with Statepointscited by 0
- 2026Authorization for Self-Modifying AI Agent Populations: Conserving Authority across Replacement, Forking, and Rollbackcited by 0
- 2026Authorization for Self-Modifying AI Agent Populations: Conserving Authority across Replacement, Forking, and Rollback29 Sep 2026
- 2026Planarian: Managing Agent State with Statepoints28 Sep 2026
- 2026When Tool Calls Succeed but Workflows Fail: Anomalies at the Agent-Tool Boundary14 Sep 2026
- 2026REVISE: Validity-Guided Recovery for Online Revisions in Agent Workflows1 Sep 2026
- 2026Safe to Resume? Breaking Execution Continuity of Agent Execution via Rollback29 Aug 2026
- 2026Resume Means Resume: A Machine-Checked Conformance Contract for Checkpoint, Interrupt, and Resume Semantics in Workflow Persistence Layers4 Aug 2026
- 2026From Agent Traces to Trust: A Survey of Evidence Tracing and Execution Provenance in LLM Agents3 Jun 2026
- 2026Sandlock: Confining AI Agent Code with Unprivileged Linux Primitives25 May 2026
- 2026Governed Capability Evolution: Lifecycle-Time Compatibility Checking and Rollback for AI-Component-Based Systems, with a Proof-of-Concept Evaluation on Embodied Agents9 Apr 2026
Similar, not cited
Close in wording, no citation either way
- 2026Beyond Single-Use Tokens: Durable Authorization State for Replay-Resistant LLM Agent Actions
- 2026DART: Semantic Recoverability for Structured Tool Agents
- 2026Crab: A Semantics-Aware Checkpoint/Restore Runtime for Agent Sandboxes
- 2026From Approval to Execution: Reconstruction-Aware Repair Analysis for LLM-Agent Software
- 2026Cordon: Semantic Transactions for Tool-Using LLM Agents
- 2026From Faulty Memories to Corrected Actions: Dependency-Guided Rollback Repair for Memory-Augmented Agents
- 2026Aborted but Not Forgotten: KV-Cache Retention Breaks Rollback Consistency in Language Agents
- 2026Context-Fractured Decomposition Attacks on Tool-Using LLM Agents: Exploiting Artifact Provenance Gaps