hunt-fintech-graphql
Hunt fintech-specific GraphQL vulnerabilities: money-movement mutations (transfers, redemptions, withdrawals, card top-ups), ledger/balance/portfolio query IDOR, decimal-precision and rounding abuse, idempotency-key bypass enabling double-spend, KYC/PII field-level authorization gaps, and admin-override mutations reachable via mass assignment. Distinct from hunt-graphql, which owns generic GraphQL discovery and IDOR/mutation methodology — this skill owns the delta introduced when a GraphQL layer sits in front of a ledger, wallet, payments, banking, brokerage, or lending backend, where a resolver bug moves real money instead of just leaking data. Use when hunting a fintech, banking, payments, wallet, neobank, brokerage, or lending target that exposes a GraphQL API, or when a schema/response includes balance, transfer, ledger, redeem, quote, KYC, or account-linking fields.
git clone --depth 1 https://github.com/elementalsouls/Claude-BugHunter /tmp/hunt-fintech-graphql && cp -r /tmp/hunt-fintech-graphql/skills/hunt-fintech-graphql ~/.claude/skills/hunt-fintech-graphqlSKILL.md
## 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.
4. **Test decimal/precision edge cases** on every amount-accepting argument — see Payload section.
Confirm server-side rounding matches client-displayed rounding; a mismatch is directly
monetizable.
5. **Probe cross-account IDOR on account/portfolio node IDs**, same as `hunt-idor`/`hunt-graphql`,
but specifically test whether a `transferFunds`-style mutation validates that the
**source account belongs to the authenticated caller** — not just that *some* account with
that ID exists. This is the fintech-specific IDOR: authz on the *source* of a debit is easy to
forget when authz on the *destination* of a credit was correctly implemented (crediting an
arbitrary account "looks safe" to a developer; debiting one clearly isn't, so it gets checked
— but sometimes only one direction does).
6. **Check field-level authorization on KYC/PII fields** by querying the shared `User`/`Account`
type from every context that returns it — not just the profile screen. A `transaction` type
that embeds `counterparty { ssnLast4 }` is a common place for the check to be missing, because
the developer authorized the top-level `transaction` query but didn't re-check field access on
the nested `counterparty`.
7. **Look for admin-tier mutations reachable via mass assignment**, not just a missing auth
check — e.g. an input object with a client-settable `status` or `override` field that a normal
user's mutation shouldn't expose but that the resolver accepts anyway
(`updateTransaction(input: {id, status: "COMPLETED", amount: "..."})`).
8. **Test currency-argument consistency.** Send a transfer/quote mutation with mismatched
`sourceCurrency`/`targetCurrency` combinations the UI never generates (e.g. self-transfer with
a currency conversion) and check whether the resolver's FX-rate lookup and the ledger write use
the same rate — a TOCTOU window here is a direct arbitrage bug.
9. **Combine alias batching with money-movement mutations** to test for double-spend — see
`hunt-race-condition` for the parallel-HTTP escalation once alias batching alone confirms the
resolver isn't serializing writes per-account.
---
## Payload & Detection Patterns
**Idempotency-key replay test:**
```graphql
mutation {
transferFunds(input: {
idempotencyKey: "test-key-001"
sourceAccountId: "acc_1"
destAccountId: "acc_2"
amount: "10.00"
}) { transEnd-to-end Android APK red-team pipeline — automated APK acquisition (Play Store + apkpure + apkmirror fallback), jadx decompilation, secret/URL/JWT/Firebase grep, pinned-cert extraction, exported-component enumeration, Frida runtime instrumentation templates, intent-injection probes. Built from an authorized external red-team engagement where 7 APKs were pulled manually, 4 download attempts truncated, and a hardcoded JWT + 30 internal API endpoints were recovered from one of the apps. Use when target has a mobile app catalogue (Play Store developer page), when you find an APK URL hosted on a web server, or when post-recon mentions "mobile app" in scope.
Run autonomous hunt loop on a target — scope check → recon → rank surface → hunt → validate → report with configurable checkpoints. Usage: /autopilot target.com [--paranoid|--normal|--yolo]
Local-tooling companion to the bug-bounty orchestrator — carries the SAME complete bug-bounty workflow, but reach for THIS variant when you also need to resolve where tools, wordlists, and clones are installed on the local machine (jhaddix, SecLists, trufflehog, ffuf, dalfox, ghauri); for pure orchestration/routing use the bug-bounty skill. Workflow it covers — recon (subdomain enumeration, asset discovery, fingerprinting, HackerOne scope, source code audit), pre-hunt learning (disclosed reports, tech stack research, mind maps, threat modeling), vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, timing side-channels, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (chatbot IDOR, prompt injection, indirect injection, ASCII smuggling, exfil channels, RCE via code tools, system prompt extraction, ASI01-ASI10), A-to-B bug chaining (IDOR→auth bypass, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth), bypass tables (SSRF IP bypass, open redirect bypass, file upload bypass), language-specific grep (JS prototype pollution, Python pickle, PHP type juggling, Go template.HTML, Ruby YAML.load, Rust unwrap), and reporting (7-Question Gate, 4 validation gates, human-tone writing, templates by vuln class, CVSS 3.1, PoC generation, always-rejected list, conditional chain table, submission checklist). Use when you need the local install path of a tool / wordlist / clone for a hunt, or as the full-workflow variant when operating from this local toolkit; for general routing use the bug-bounty skill. 中文触发词：漏洞赏金、安全测试、渗透测试、漏洞挖掘、信息收集、子域名枚举、XSS测试、SQL注入、SSRF、安全审计、漏洞报告
Use at the START of any bug bounty hunting session, when switching targets, or when feeling lost about what to do next. Master orchestrator that combines the 5-phase non-linear hunting workflow with the critical thinking framework (developer psychology, anomaly detection, What-If experiments). Routes to all other skills based on current hunting phase. Also use when asking "what should I do next" or "where am I in the process.
Complete bug bounty workflow — recon (subdomain enumeration, asset discovery, fingerprinting, HackerOne scope, source code audit), pre-hunt learning (disclosed reports, tech stack research, mind maps, threat modeling), vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, timing side-channels, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (chatbot IDOR, prompt injection, indirect injection, ASCII smuggling, exfil channels, RCE via code tools, system prompt extraction, ASI01-ASI10), A-to-B bug chaining (IDOR→auth bypass, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth), bypass tables (SSRF IP bypass, open redirect bypass, file upload bypass), language-specific grep (JS prototype pollution, Python pickle, PHP type juggling, Go template.HTML, Ruby YAML.load, Rust unwrap), and reporting (7-Question Gate, 4 validation gates, human-tone writing, templates by vuln class, CVSS 3.1, PoC generation, always-rejected list, conditional chain table, submission checklist). Use for ANY bug bounty task — starting a new target, doing recon, hunting specific vulns, auditing source code, testing AI features, validating findings, or writing reports. 中文触发词：漏洞赏金、安全测试、渗透测试、漏洞挖掘、信息收集、子域名枚举、XSS测试、SQL注入、SSRF、安全审计、漏洞报告
Bugcrowd-specific reporting tactics complementing report-writing: VRT category search-and-fallback strategy when no exact match exists, manual severity override when VRT defaults underrate impact, severity-request paragraph as first body section, OOS-clause rebuttal templates (rate limiting on auth-flow endpoints, debug-info framing, user-enumeration with sensitive PII, theoretical-issue counter), chained-finding cross-reference patterns, target selection for QA-vs-prod programs, researcher-side hygiene (Bugcrowdninja email alias, account state restoration, friendly-tester posture). Use when filing a Bugcrowd submission, when VRT default seems wrong, when triager closes as OOS or downgrades severity, when chaining linked submissions, or when scope distinguishes production from QA. Pairs with report-writing and triage-validation.
Build an exploit chain — given bug A, finds B and C to combine for higher severity and payout. Knows common chain patterns: IDOR→ATO, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth. Usage: /chain
Cloud IAM red-team attack chain across AWS, Azure, GCP — focused on EXTERNAL exploitation paths and post-credential-discovery privilege analysis. Covers IAM enumeration (aws iam, az role, gcloud iam), STS/AssumeRole chaining, Azure Managed Identity abuse (via SSRF/leak), GCP service account JSON abuse, IMDSv1/v2 attacks via SSRF, K8s ServiceAccount token privilege analysis once held (token discovery / cluster exposure is owned by hunt-k8s), role-trust-policy confused-deputy, cross-account assume-role enumeration, IAM privilege escalation patterns (24+ AWS, 8+ Azure, 6+ GCP), and AWS Cognito Identity Pool unauthenticated-role attack chain (GetId → GetCredentialsForIdentity → IAM role abuse). Built for the case where recon yields a credential (key, JSON, token) and you need to know what it grants and how to escalate. Use when an AWS key / Azure secret / GCP service account JSON / K8s SA token surfaces from a code repo, JS bundle, APK, breach corpus, or SSRF chain.