You are helping a penetration tester exploit misconfigured Active Directory
日本語の概要は準備中です。原文の説明を表示しています。
Generic GraphQL bugs (IDOR, mass assignment, introspection, batching abuse — see hunt-graphql)
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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:
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.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.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.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:
bankLink, plaidLinkToken mutations)ledger or payments subgraph — check for the subgraph's own introspection being reachable directly, bypassing the gateway's stitched-down schemaMoney/Decimal/BigDecimal GraphQL scalar in the schema (scalar Money) — the parser for this scalar is worth fuzzing directlyRun 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.
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).
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.
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.
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.
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).
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.
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: "..."})).
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.
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.
Idempotency-key replay test:
mutation {
transferFunds(input: {
idempotencyKey: "test-key-001"
sourceAccountId: "acc_1"
destAccountId: "acc_2"
amount: "10.00"
}) { transactionId status }
}
Send twice with the identical idempotencyKey. Two successful, distinct transactionId values
= idempotency not enforced.
Decimal-precision / rounding probes:
mutation { transferFunds(input: {sourceAccountId:"acc_1", destAccountId:"acc_2", amount: "0.001"}) { transactionId } }
mutation { transferFunds(input: {sourceAccountId:"acc_1", destAccountId:"acc_2", amount: "9999999999999999.99"}) { transactionId } }
mutation { transferFunds(input: {sourceAccountId:"acc_1", destAccountId:"acc_2", amount: "1e2"}) { transactionId } }
mutation { transferFunds(input: {sourceAccountId:"acc_1", destAccountId:"acc_2", amount: "-50.00"}) { transactionId } }
Sub-cent amounts test truncate-vs-round handling (repeat N times to accumulate a rounding-error
balance drift); scientific notation and oversized values test whether the Money/Decimal
scalar parser falls back to a native float/int with overflow or precision-loss behavior; negative
amounts test whether the resolver assumes sign server-side or trusts the client's.
Alias-batched double-spend probe (confirm before escalating to parallel HTTP):
mutation {
r1: redeemRewards(input: {rewardId: "rwd_1", accountId: "acc_1"}) { success }
r2: redeemRewards(input: {rewardId: "rwd_1", accountId: "acc_1"}) { success }
r3: redeemRewards(input: {rewardId: "rwd_1", accountId: "acc_1"}) { success }
}
If more than one alias succeeds against a single-use reward/coupon, the resolver doesn't
serialize per-account/per-resource writes within a batched request — see hunt-race-condition
for combining this with parallel HTTP POSTs to confirm real double-spend impact.
Source-account authorization probe (asymmetric IDOR check):
mutation {
transferFunds(input: {
sourceAccountId: "VICTIM_ACCOUNT_ID"
destAccountId: "ATTACKER_CONTROLLED_ACCOUNT_ID"
amount: "1.00"
}) { transactionId status }
}
Run as the attacker's own session/token. Success = the resolver validated the destination is attacker-controlled (obviously required) but never validated that the source belongs to the caller.
Nested field-level PII probe:
query {
transaction(id: "txn_123") {
amount
counterparty { displayName ssnLast4 routingNumber kycStatus }
}
}
Query as a user with no relationship to the counterparty beyond a shared transaction; success on
the nested PII fields is the finding even if the top-level transaction query correctly scoped
the transaction itself.
Mass-assignment probe on admin-shaped input fields:
mutation {
updateTransaction(input: {id: "txn_123", status: "COMPLETED", amount: "0.01"}) { id status }
}
Send as a non-admin user against a mutation the client UI never exposes these fields for; a schema that accepts them anyway is mass assignment onto ledger state.
Money/Decimal scalar falls back to native float parsing under edge-case input
(scientific notation, oversized strings), reintroducing floating-point rounding error into a
system that was supposed to guarantee fixed-point precision.User/Account
type's sensitive fields are protected when queried directly (me { ssnLast4 }) but not when
the same type is returned nested inside an unrelated query (transaction { counterparty {...} }).Money-movement findings need a stricter bar than a typical GraphQL IDOR — "the query returns someone else's balance" is real impact; "I sent a malformed amount and got a 400" is not.
200/success response body) is the proof.Money scalar is a
hunt-source-leak-class finding, not a fintech-logic one — don't conflate the two in a report.hunt-graphql — parent skill for generic GraphQL discovery, introspection bypass, node-ID
IDOR, and alias-batching mechanics. Load this skill first; hunt-fintech-graphql assumes that
methodology and only adds the money-movement-specific delta.hunt-business-logic — coupon/reward double-redemption and other logic-flaw patterns
generalize directly to redeemRewards/applyCoupon-style mutations here.hunt-race-condition — the escalation path once alias batching alone confirms a
money-movement mutation doesn't serialize writes: combine with parallel-HTTP / single-packet
attack for a deterministic double-spend PoC.hunt-api-misconfig — mass assignment and JWT-claim tampering patterns apply directly to
admin-shaped GraphQL input objects reachable by normal users.hunt-idor — the source-account-vs-destination-account asymmetric authz pattern (step 5) is
a fintech-specific instance of the general IDOR-on-mutation-argument class.evidence-hygiene — balance screenshots and ledger-entry PoCs need the same cookie/PII
redaction discipline as any other capture, plus care that a real account number/balance from a
live financial account is never included verbatim.triage-validation — apply Gate 0 above before drafting; a fintech program's triage team
will kill anything without a demonstrated ledger state change immediately.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
You are helping a penetration tester exploit misconfigured Active Directory
日本語の概要は準備中です。原文の説明を表示しています。
You are helping a penetration tester enumerate an Active Directory domain and
日本語の概要は準備中です。原文の説明を表示しています。
You are helping a penetration tester establish persistent access in Active
日本語の概要は準備中です。原文の説明を表示しています。
You are helping a penetration tester exploit ADCS through template/CA access
日本語の概要は準備中です。原文の説明を表示しています。
You are helping a penetration tester establish persistence through AD CS
日本語の概要は準備中です。原文の説明を表示しています。
You are helping a penetration tester exploit misconfigured AD CS certificate
日本語の概要は準備中です。原文の説明を表示しています。