hunt-fintech-graphql

⚠️ AUTHORIZED USE ONLY This skill is for educational purposes or authorized security assessments only. You must have explicit, written permission from the system owner before using this tool. Misuse of this tool is illegal and strictly prohibited.

Mandatory confirmation gate Before running any command that probes, exploits, changes, persists on, extracts data from, or attempts credential access against a target:

1. Ask the user to state the exact target URL, IP, account, or resource.
2. Ask the user to confirm written authorization and the permitted scope.
3. Show the exact command(s) and explain their expected effect.
4. Wait for explicit confirmation in the current conversation.

Without that confirmation, remain read-only and provide defensive guidance only. Prefer a sandbox, disposable VM, or controlled lab.

Why Fintech GraphQL Is a Different Risk Class

Generic GraphQL bugs (IDOR, mass assignment, introspection, batching abuse — see hunt-graphql) still apply here, but the blast radius changes completely: a resolver bug in a SaaS app leaks data, the same class of bug in a ledger mutation moves money. Three properties make fintech GraphQL backends a distinct hunting surface:

• Money-movement mutations are almost always resolvers over a double-entry ledger. A single GraphQL mutation (transferFunds, redeemRewards, withdrawToBank) can trigger multiple ledger writes (debit + credit + fee) that must be atomic. GraphQL's flexible input shape and alias batching make it easy to desynchronize those writes.
• Decimals are attacker-controlled input, not display formatting. Amounts, exchange rates, interest, and rewards points are usually passed as GraphQL scalars (Float, String, custom Decimal/Money scalar). How the resolver parses and rounds that value is exploitable surface in its own right — this barely exists in non-financial GraphQL APIs.
• KYC/PII fields sit next to routine account fields in the same type. User or Account types commonly expose ssnLast4, routingNumber, kycStatus, governmentIdUrl, or linkedBankAccount alongside displayName and email — one missing field-level authorization check on a type used everywhere in the schema fans out to every query that touches it.

Attack Surface Signals

URL / schema naming patterns (in addition to hunt-graphql's generic /graphql list):

/graphql/ledger
/graphql/payments
/api/wallet/graphql
/internal/ledger-graphql
/banking/graphql

Field/type names worth grepping schema introspection or JS bundles for:

balance, availableBalance, pendingBalance, ledgerEntry, ledgerEntries
transferFunds, withdraw, redeem, topUp, reverseTransaction, adjustBalance
kycStatus, ssnLast4, routingNumber, accountNumber, governmentIdUrl
quoteExchangeRate, interestAccrued, rewardsPoints, portfolioValue
idempotencyKey, clientMutationId

Tech-stack tells specific to this vertical:

• Plaid/Stripe/Dwolla/Marqeta wrapped behind an internal GraphQL gateway (bankLink, plaidLinkToken mutations)
• Apollo Federation with a dedicated ledger or payments subgraph — check for the subgraph's own introspection being reachable directly, bypassing the gateway's stitched-down schema
• Custom Money/Decimal/BigDecimal GraphQL scalar in the schema (scalar Money) — the parser for this scalar is worth fuzzing directly

Run hunt-graphql's discovery + introspection methodology first to get the schema; everything below assumes you already have (or have partially enumerated) a schema with money-movement types.

Step-by-Step Hunting Methodology

1. Map every mutation that touches balance, whether directly or as a side effect. Not just transfer*/withdraw* — also redeemRewards, applyCoupon, upgradeTier, closeAccount (often refunds a balance), disputeTransaction (often provisionally credits).

2. For each money-movement mutation, identify the ledger write shape. Does one mutation call produce one ledger entry or several (debit sender, credit receiver, fee entry)? Multi-entry writes are the ones worth racing — see Stage 4.

3. Test idempotency-key handling. Send the identical mutation (same idempotencyKey / clientMutationId) twice, back-to-back and with a delay. A ledger write on the second call means idempotency isn't enforced server-side — replay = double-execute.

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