Individual skill
business-logic-testing
Discover the application intended business rules and violate their assumptions - money and value manipulation, limit bypass, identity and relationship abuse, state misuse - proving persisted out-of-policy outcomes rather than status-code blips.
internal/tools/skills/data/application-security/business-logic-testing/SKILL.md
Source commit d42f381ad34843e71a42658e5c57290c713e85af
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- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- Yes
- Observed behavior
- Instructions only
- Last checked
- Nov 9, 2026
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Repository context
- Repository stars (not skill ratings)
- 1,320
- Repository last updated
- Nov 8, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- cybersecurity Repository topic
- security Repository topic
- bug-bounty Repository topic
- automation Repository topic
- autonomous-pentesting Repository topic
- ai-agent Repository topic
- ai-security Repository topic
- ethical-hacking Repository topic
- golang Repository topic
- penetration-testing Repository topic
- business-logic Declared skill tag
- price-manipulation Declared skill tag
- coupon-abuse Declared skill tag
- referral-abuse Declared skill tag
- limit-bypass Declared skill tag
- workflow-bypass Declared skill tag
- negative-testing Declared skill tag
- owasp Declared skill tag
- operations Derived category
- testing Derived category
- security Derived category
- security-application Derived category
Files and excerpt
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SKILL.mdcore · 8,098 bytes
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# Business Logic Testing
## Purpose
Business logic flaws are rules the application MEANT to enforce but does not: prices, quantities, limits, coupons, quotas, identities, and states. Scanners cannot find them because the bug is not in a payload pattern - it is in the gap between intended rule and enforced rule. This skill teaches how to discover the intended rules black-box, then violate one assumption at a time and verify the backend actually persisted the out-of-policy outcome.
## Entry Conditions
- The application has any business rules: prices, quantities, coupons, credits, quotas, trials, referrals, invites, approvals, refunds, balances, votes, subscriptions
- You can perform at least one legitimate transaction to establish a baseline
## Step 1: Discover the Intended Rules
Black-box rule discovery from: UI copy ("one per customer", "limit 3", "non-refundable"), error messages on first violation (the app tells you the rule it thinks it enforces), pricing pages and ToS, how a legit transaction progresses (which fields are client-supplied vs recomputed), and client-side validation code (what the frontend refuses reveals what the backend SHOULD check).