mlsanityData to 14 Oct 2026

FinHarness: An Inline Lifecycle Safety Harness for Finance LLM Agents

arXiv 2605.27333 ↗First posted 26 May 2026cs.CLcited by 1

On the map: LLM agents and tool use → Financial trading and forecasting agents

Abstract (arXiv)

Finance LLM agents must simultaneously block prompt-induced unauthorized actions and approve legitimate multi-step business workflows. However, boundary filters often miss irreversible mid-trajectory tool calls, while post-hoc LLM judges perform auditing only after termination -- too late for intervention and at a computational cost that scales linearly with trace length. We present FinHarness, an inline safety harness that wraps a finance agent end-to-end with three components: a Query Monitor that fuses single-turn intent with cross-turn drift, a Tool Monitor that evaluates each prospective tool call, and a Cascade module that integrates per-step risk and adaptively routes verification between a lightweight and an advanced-tier LLM judge. Fired risk factors are re-injected into the agent input as ex-ante evidence, enabling the agent to refuse, re-plan, or approve on its own. On FinVault, routed FinHarness cuts ASR from 38.3% to 15.0% while largely preserving benign approval (41.1% → 39.3%), and uses 4.7× fewer advanced-judge calls than an always-advanced ablation.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Financial trading and forecasting agents, one of 16 directions in LLM agents and tool use. Builds on 10 of its 16 references that are in the map. First posted on arXiv 26 May 2026.

Builds on

10 of 16 references.

Closest ancestors · 1

Same direction, newest first

  1. 2026FinVault: Benchmarking Financial Agent Safety in Execution-Grounded Environments9 Jan

Other references · 9

  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
  3. 2023Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injectioncited by 1,443
  4. 2024StruQ: Defending Against Prompt Injection with Structured Queriescited by 375
  5. 2024Agent-SafetyBench: Evaluating the Safety of LLM Agentscited by 306
  6. 2024Defending Against Indirect Prompt Injection Attacks With Spotlightingcited by 267
  7. 2025LlamaFirewall: An open source guardrail system for building secure AI agentscited by 127
  8. 2025IPIGuard: A Novel Tool Dependency Graph-Based Defense Against Indirect Prompt Injection in LLM Agentscited by 54
  9. 2026SafeHarness: Lifecycle-Integrated Security Architecture for LLM-based Agent Deploymentcited by 15

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

Similar, not cited

Close in wording, no citation either way

  1. 2026FinRED: An Expert-Guided Benchmark Generation and Evaluation Framework for Financial LLM Red-Teaming
  2. 2025Standard Benchmarks Fail -- Auditing LLM Agents in Finance Must Prioritize Risk
  3. 2026ReguSim: Evaluating LLM Agent Rule Grounding in Financial Compliance
  4. 2026Replayable Financial Agents: A Determinism-Faithfulness Assurance Harness for Tool-Using LLM Agents
  5. 2026Who Tests the Testers? Systematic Enumeration and Coverage Audit of LLM Agent Tool Call Safety
  6. 2026The Verifier Tax: Horizon Dependent Safety Success Tradeoffs in Tool Using LLM Agents
  7. 2026NEXUS: Structured Runtime Safety for Tool-Using LLM Agents
  8. 2026Toward Safe LLM Agents: A Survey of Specification, Verification, and Enforcement