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Checklist, in AI in Markets

Prompt Injection Defense for Finance Agents

A finance agent that retrieves documents or takes user input is an attack surface, and a successful injection can exfiltrate data or trigger a trade. This checklist hardens the pipeline against injection specifically, complementing the broader deployment checklist.

12 items. Published May 26, 2026. By AI Fin Hub Research.

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Sections

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Section 1

Phase 1: Trust boundaries

3 items

Use the Prompt Injection Tester: Red-team a finance agent against 23 documented prompt-injection attacks — direct override, role confusion, indirect injection via retrieved content.

Use the Price-Blind Research Auditor: Paste a research prompt or agent context bundle. The auditor flags price numbers, directional words, and outcome-leaking phrases that cause LLMs.

Section 2

Phase 2: Least privilege

3 items

Section 3

Phase 3: Output and data controls

3 items

Use the Structured Schema Validator for Finance: Paste LLM JSON output and validate against four pre-built finance schemas — research output, trade decision, risk snapshot, peer comparison — with sanity.

Section 4

Phase 4: Red-teaming

3 items

Use the Prompt Regression Tester: Run the same prompt against multiple models (Claude 4.5/4.6/4.7, GPT-5, Gemini 2.5) with your own keys. Diff outputs, score drift, catch regressions.

Tips

Small moves that make the checklist easier to finish

Indirect injection is the attack that gets missed. The hostile instruction does not come from the user, it comes from a document the agent was told to read, which is exactly the content you trust by default.
Least privilege is the only defense that holds when prevention fails. Assume an injection will eventually succeed and design so that when it does, the model simply cannot reach anything that matters.
Never put a credential in the model context. The cleanest exfiltration defense is having nothing to exfiltrate, so keep secrets in the deterministic layer the model cannot see.

Sources

  1. OWASP Top 10 for Large Language Model Applications , OWASP Foundation (2023)
  2. Not What You've Signed Up For: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection , Greshake et al., AISec Workshop (2023)

Keep the topic connected

  • Checklist LLM for Finance Deployment Checklist

    A pre-flight checklist for putting a large language model into a finance workflow: scoping, grounding, input security, numerical verification, and drift monitoring.

  • Checklist RAG for Filings Setup Checklist

    RAG for filings checklist: chunk on structure, tune retrieval, enforce citations, verify numbers, and treat retrieved text as untrusted.

  • Learn Prompt Injection

    Prompt injection: when untrusted text in a prompt overrides system instructions. The attack patterns and the structural defenses that work in production.

  • Checklist Finance Agent Fallback Resilience Checklist

    LLM fallback chain checklist: define a provider fallback, handle rate limits and timeouts, set degradation modes, and test the failure paths.