Business Logic Testing — Invariants, State-Machine Abuse, Race Conditions

The vulnerability classes scanners cannot find. A scanner matches syntax; a logic flaw is a mismatch between what the app is supposed to guarantee and what its code actually enforces under adversarial or concurrent use. This skill is the dynamic counterpart to owasp-audit's source-side race patterns (TOCTOU, atomic queue claim, reserve-then-act) and the depth behind web-pentest Phase 8.

Work invariant-first: name the guarantee, then try to break it. A finding is not "I sent a weird request" — it is "I violated a stated invariant and proved durable state changed."

Authorization Check

Concurrency and logic testing mutates real state. Before sending anything:

1. Written authorization naming this specific application and that business-logic and concurrency testing are in scope.
2. Prefer a staging or test-mode environment. Use payment test mode (e.g. Stripe test keys), seeded test tenants, and disposable accounts you own. Never exercise a production money flow, inventory ledger, or third-party billing API unless the written scope explicitly names it.
3. A request-count cap agreed in advance. Concurrency proofs need tens of parallel requests, not thousands — name the ceiling and stay under it.
4. Accounts you control for every role and tenant you will test (owner, non-owner, admin, two tenants).

If any of these is missing, stop and ask. See Boundaries below.

Sending live requests is deliberately outside this skill's pre-approved tools (Read, Grep, Glob only) — the human runs the parallel requests, or approves each tool invocation, so a throughput test never fires unattended.

Step 1 — Model the invariants

Before touching a request, write down what the system promises. Four families cover most money and workflow bugs:

• Conservation of value. Money, credits, points, inventory, and quota are neither created nor destroyed except through an authorized path. A $10 refund must remove exactly $10 of credit; redeeming a coupon must decrement its remaining uses.
• Uniqueness. A coupon redeems once per rule; a username, invite, or idempotency key is claimed by exactly one principal; an order is fulfilled once.
• Monotonicity. Some counters only move one way — a used voucher never returns to unused, a shipped order never returns to pending, a consumed one-time token never re-validates.
• Exclusivity. A seat, a lock, a lease, or a "pending approval" row is held by one actor at a time; two parties cannot both own the same mutually-exclusive resource.

For each invariant, note where it is enforced (a DB unique constraint? an application if? only the UI?) and what proves a violation (a ledger that no longer sums to zero, two rows where one should exist). An invariant enforced only in the UI or only in a single handler is the lead.

Step 2 — Actor x Action x Resource matrix

Enumerate the grid and look for the cells the app forgot:

• Actors: anonymous, authenticated user, resource owner, non-owner, admin, two separate tenants, a user mid-workflow.
• Actions: create, read, update, delete, approve, cancel, refund, redeem, transfer, advance-state.
• Resources: each object with a lifecycle or a balance — order, invoice, coupon, subscription, document, approval request, wallet.

Fill each cell with the expected outcome (allow / deny), then test the deny cells and the state-sensitive allow cells. The interesting failures: a non-owner reaching an owner action (overlaps IDOR/BOLA — see web-pentest Phase 4), an actor performing an action valid only in a different state, or the same actor performing a once-only action twice.

Step 3 — State-machine abuse

Draw the intended state graph (cart -> checkout -> paid -> shipped; draft -> submitted -> approved). Then attack the edges:

• Skip a step. Call the step-4 endpoint directly without completing step 2. Can you reach paid without a charge, or approved without a reviewer?
• Reorder steps. Apply a discount after the total is locked; change the shipping address after payment authorization but before capture.
• Replay a step. Re-POST a terminal transition. Does "confirm" run twice? Does a one-time token validate again?
• Limit-slicing. A limit checked per-request but not in aggregate: split one over-limit action into many under-limit ones (withdraw the daily max in several smaller transfers; exceed a per-upload cap across many uploads that share no running total).
• Approve your own request. Tamper with approver_id / reviewer_id so the requester and approver are the same principal.

Each of these is a candidate for the concurrency amplifier in Step 6 — a window that is hard to hit sequentially is trivial to hit with parallel requests.

Step 4 — Numeric and value issues

• Float vs. decimal. Prices or balances stored or computed as floats accumulate rounding error. Probe amounts like 0.1 + 0.2, long-fraction quantities, and values near rounding boundaries; watch for a cent appearing or vanishing.
• Rounding direction. A per-line-item round that always rounds in the customer's favor, summed over many items, leaks value. Many small items can be cheaper than the honest total.
• Negative and zero amounts. Can you order quantity -1, transfer a negative sum (crediting yourself), or apply a discount larger than the subtotal to drive the total below zero?
• Cross-currency refund arbitrage. Pay in a currency that converts one way, refund in another (or at a later rate), and keep the spread. Test when charge and refund use different rate snapshots or different currencies.
• Type / precision coercion. Scientific notation (1e3), extra precision, leading zeros, or integer overflow at the boundary of the money type.

Step 5 — Stale authorization and saga gaps

• Stale feature gates and roles. After a downgrade, cancellation, or role change, does the old capability keep working until a cache expires? Test the gated action immediately after revoking the entitlement, and with a token minted before the change.
• Event-driven saga gaps. Multi-service workflows coordinated by events (order -> payment -> inventory -> fulfillment) have no single transaction. Look for: a step that commits before a prior step's compensation can run, a compensation (refund, release-inventory) that never fires on partial failure, and a consumer that is not idempotent so a redelivered event double-applies. The dynamic tell is a state that is internally inconsistent across services after an interrupted or duplicated flow.

Step 6 — Concurrency methodology

Most logic invariants are enforced with a check-then-act sequence that is safe sequentially and unsafe in parallel. The goal is to land N requests inside the same check-then-act window so the check passes N times before any act commits.

Patterns to hunt (source-side equivalents live in owasp-audit A06/A02/A08):

• Idempotency key scoped to the path, not the principal. If the key is keyed by (endpoint, key) rather than (principal, endpoint, key), another user's key — or a replay of your own — reuses a completed result. Submit two different operations under one key; submit one key across two accounts.
• Cache-before-commit. The app writes a "reserved/pending" marker to a cache, then commits to the DB. Two requests both read "available" from the stale cache before either commit lands.
• Lost update (read-modify-write). balance = read(); write(balance - amount) with no atomic decrement or version check — concurrent writers each start from the same read and the last write wins, losing the others' effect.
• Saga compensation timing. Fire the parallel burst during the window between a forward step and its compensation.
• Redis locks without NX/EX or fencing tokens. A lock set without atomic acquire-and-expire, or without a fencing token, lets two holders believe they own it (one acquires, the other sets over it; or a GC-paused holder acts after its lease expired).
• READ COMMITTED anomalies. The default isolation level permits non-repeatable reads and write skew — two transactions each read a constraint as satisfied and both write, violating it. Uniqueness enforced by SELECT ... then INSERT (instead of a DB UNIQUE constraint) breaks here.
• Upsert races. "Insert if absent else update" implemented in app code (not an atomic INSERT ... ON CONFLICT) double-inserts under concurrency.

Landing the requests on the same window. The web-request equivalent of a starter pistol:

• HTTP/2 single-packet attack. Put the final frame of many requests into one TCP packet so the server receives them simultaneously, removing network jitter from the race.
• Last-byte synchronization (HTTP/1.1). Send all but the last byte of each request ahead of time over kept-alive connections, then release the last bytes together.
• Connection warming. Send a throwaway request first so TLS/connection setup and any lazy initialization are already done before the timed burst.

Tooling, a worked Turbo Intruder config, and a minimal httpx/curl --parallel runner are in references/concurrency.md — all scoped to authorized-test use and the agreed request cap.

Validation and false positives — per class

Hold every candidate to the evidence bar before it becomes a finding. Use the verdict vocabulary: a candidate is confirmed, needs_validation, or rejected (see references/verification.md). Severity attaches only to confirmed findings; calibrate with references/severity-calibration.md.

General validation standard (all classes): 1 request is correctly denied, then N concurrent requests succeed where only 1 should — and the durable state change is proven (ledger no longer sums correctly, two rows where uniqueness required one, a counter past its monotone bound, a balance that moved further than any single authorized action allows). A changed response code alone is not proof; read the persisted state back.

The two false-positive traps to always rule out:

1. Truly idempotent operations. An enforced ETag/If-Match, a DB UNIQUE constraint, or INSERT ... ON CONFLICT DO NOTHING means the duplicates collapse to one commit — the parallel requests look accepted (all 200) but only one took effect. Always read the durable state, never trust the status code.
2. Visual-only glitches. A doubled toast, an optimistic UI that shows two items, or a transient count before a refetch is not a finding if the server state is correct. No durable state change, no finding — record it as a hardening note at most, never a severity.

A candidate you could not land under the agreed request cap is needs_validation with a validation_plan (the exact burst to run in staging), not a confirmed finding.

Output Format

Report with the shared findings vocabulary; see references/findings-format.md for the findings.json record and how to validate/export it.

# Business Logic & Race Condition Test Report
## Target / environment: [app + staging vs prod, test-mode confirmation]
## Authorization: [scope reference, request-count cap]

### Invariant register
| Invariant | Family | Enforced where | Violation proof |

### Findings
#### [verdict] [Title]
**Invariant violated:** [conservation / uniqueness / monotonicity / exclusivity]
**Endpoint(s):** `METHOD /path`
**Preconditions:** [accounts, state, concurrency needed]
**Reproduction:** [the controlled burst — count, sync method; or the step sequence]
**Durable-state proof:** [the balance/row/counter read back that shows the violation]
**Verdict:** confirmed | needs_validation (+ blockers, validation_plan) | rejected (+ ruled_out_by {control, location})
**Severity:** [only if confirmed — see severity-calibration.md]

### Hardening notes (not findings)
[Visual-only glitches, defense-in-depth gaps with no traced durable impact]

Boundaries

• Refuse to run concurrency or logic tests against a production money flow, inventory ledger, or live third-party billing API without explicit written scope naming it. Default to staging / test mode.
• Refuse to exceed the agreed request-count cap or to turn a proof into a sustained load — a controlled double-spend proof is a dozen requests, not a stress test (that is a DoS; see web-pentest Boundaries).
• Never touch third-party systems (the payment provider's own API, upstream SaaS) as a target — they are out of scope by default even when the app in scope calls them.
• Proof of concept is the minimum burst that demonstrates the violation, not a reusable exploit for repeated extraction.
• If a test moves real money or real inventory, stop and report; do not "clean up" by issuing compensating transactions that mutate more state.

Cross-references

• owasp-audit A06/A02/A08 — source-side race patterns: TOCTOU, atomic queue claim (UPDATE ... WHERE status='pending' RETURNING), reserve-then-act, external-resource-create TOCTOU. Read the code to locate the check-then-act window this skill proves dynamically.
• web-pentest Phase 8 (business logic) and its "Combined white-box + black-box mode" — when source and a running instance are both available, code findings point to the exact window to race.
• api-audit — idempotency, BOLA, and API-level object/function authorization.
• finding-triage — close each candidate to a disposition with contextual severity.

References

• Strix (Apache-2.0) — vulnerabilities/race_conditions.md and vulnerabilities/business_logic.md (https://github.com/usestrix/strix). Techniques paraphrased, not copied. This skill deliberately does not adopt Strix's never-refuse / never-question-authorization posture: authorization, staging preference, and request caps are enforced here.
• PortSwigger Web Security Academy — race conditions (single-packet attack) and business-logic labs.
• OWASP Web Security Testing Guide (WSTG) — Business Logic Testing section.