mlsanityData to 7 Oct 2026

Ghost Tool Calls: Issue-Time Privacy for Speculative Agent Tools

arXiv 2606.02483 ↗First posted 1 Jun 2026cs.CR cs.AI cs.CLcited by 0

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

Abstract (arXiv)

Tool-augmented language agents speculatively issue likely future tool calls to hide latency, but those calls leak inferred user intent to external services before the agent commits to the branch. Every external observer that received the call retains the disclosure after the agent abandons the branch. Timing is the issue, not authorization: no commit-time cleanup, read-only restriction, or access-control allow-list unsends what an observer already holds. We call these invocations ghost tool calls and propose Speculative Tool Privacy Contracts, a runtime abstraction that treats observation before commitment as a first-class effect, distinct from state mutation. We implement the contracts in a prototype runtime and evaluate twelve policies across three corpora. Speculative dispatch increases what an observer can infer about user intent; post-hoc filters, read-only restrictions, and access-control allow-lists leave that inference intact; only issue-time policies that change or suppress the speculative call's argument or destination projection before dispatch reduce it.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 16 of its 27 references that are in the map. First posted on arXiv 1 Jun 2026.

Builds on

16 of 27 references.

Closest ancestors · 6

Same direction, newest first

  1. 2026Ghost in the Agent: Redefining Information Flow Tracking for LLM Agents25 Apr
  2. 2026Observable Channels, Not Just Storage: Evaluating Privacy Leakage in LLM Agent Pipelines24 Mar
  3. 2026ToolSafe: Enhancing Tool Invocation Safety of LLM-based agents via Proactive Step-level Guardrail and Feedback15 Jan
  4. 2026Towards Verifiably Safe Tool Use for LLM Agents12 Jan
  5. 2025Exposing LLM User Privacy via Traffic Fingerprint Analysis: A Study of Privacy Risks in LLM Agent Interactions8 Oct
  6. 2023Identifying the Risks of LM Agents with an LM-Emulated Sandbox25 Sep

Other references · 10

  1. 2024τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domainscited by 1,280
  2. 2024The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG)cited by 159
  3. 2018Spectre Attacks: Exploiting Speculative Executioncited by 47
  4. 2026Atomix: Timely, Transactional Tool Use for Reliable Agentic Workflowscited by 27
  5. 2026Parallelizing Tool Execution and LLM Generation for Low-Latency Agent Servingcited by 16
  6. 2025Optimizing Agentic Language Model Inference via Speculative Tool Callscited by 11
  7. 2025Dynamic Speculative Agent Planningcited by 10
  8. 2024When Speculation Spills Secrets: Side Channels via Speculative Decoding In LLMscited by 6
  9. 2026ToolSpec: Accelerating Tool Calling via Schema-Aware and Retrieval-Augmented Speculative Decodingcited by 4
  10. 2026Concurrency without Model Changes: Future-based Asynchronous Function Calling for LLMscited by 2

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  1. 2026The Claws in Plain Sight: Unauthorized Context Disclosure through LLM Agent Tool Calls
  2. 2026OCELOT: Inference-Leakage Budgets for Privacy-Preserving LLM Agents
  3. 2026AgentSCOPE: Evaluating Contextual Privacy Across Agentic Workflows
  4. 2026OverAct: Measuring and Mitigating Proactive Over-Authorization in LLM Tool-Calling Agents
  5. 2026AgentFlow: A Flow-Centric Policy Language and Framework for Securing LLM Agent Systems
  6. 2026When Tool Outputs Become Commands: Separating Action Induction from Runtime Authorization in Tool-Augmented LLM Agents
  7. 2026Grimlock: Guarding High-Agency Systems with eBPF and Attested Channels
  8. 2026Speculative Interaction Agents: Building Real-Time Agents with Asynchronous I/O and Speculative Tool Calling