hunt-business-logic

hunt-business-logic is a skill for Claude Code, Codex from adriannoes/awesome-agentic-ai. It costs 31 tokens per session (3,022 once invoked), scanned A, original, MIT.

A security testing guide for finding business-logic flaws: bugs where an application follows its rules incorrectly, such as allowing an action without the required payment, verification, or permission.

In plain words
What is it for?
Use it to examine checkout, subscriptions, identity checks, callbacks, webhooks, and internal portals for ways to bypass intended business rules.
Why use it?
It helps uncover mistakes that ordinary input validation checks may miss, especially when several steps or user roles interact.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Use it to examine checkout, subscriptions, identity checks, callbacks, webhooks, and internal portals for ways to bypass intended business rules.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/adriannoes/awesome-agentic-ai/hunt-business-logic
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add adriannoes/awesome-agentic-ai --skill hunt-business-logic
Clone the repo
git clone --depth 1 https://github.com/adriannoes/awesome-agentic-ai

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for hunt-business-logic

README.md
[![agentmods](https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/hunt-business-logic/github.svg)](https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/hunt-business-logic)
Your own site
<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/hunt-business-logic"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/hunt-business-logic/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for hunt-business-logic

Your own site · 80×15
<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/hunt-business-logic"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/hunt-business-logic.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 31 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,022 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 2 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Data Exfiltration · line 73
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 109
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00031 $0.03022
Opus 5 $0.00015 $0.01511
Sonnet 5 $0.00006 $0.00604
Haiku 4.5 $0.00003 $0.00302

Measured 9d ago against content hash 2a8022e84ffb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

hunt-business-logic scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -s -X POST https://target.com/api/subscribe \
cursor-claude-codex/skills/bug-hunter/skills/hunt-business-logic/SKILL.md · 199 lines

How it starts

The opening of the file, as written. The whole thing — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Crown Jewel Targets

Business logic vulnerabilities pay highest in platforms where financial transactions, identity verification, and access controls intersect with real-world consequences. The richest targets are:

  • E-commerce & payment platforms (Valve/Steam, Shopify) — payment flow manipulation, free goods, price tampering
  • Marketplace & gig economy apps (Airbnb, Uber) — identity/verification bypass enabling fraud or unsafe interactions
  • SaaS with tiered access (Mozilla Monitor) — bypassing verification to unlock monitoring features without entitlement
  • High-traffic consumer apps (Snapchat, Yelp) — rate-limit bypass enabling spam, enumeration, or abuse at scale

Asset types that pay: checkout flows, subscription endpoints, callback/verification systems, webhook handlers, employee/internal portals exposed to the internet, and any endpoint that trusts client-supplied data to make authorization decisions.


Attack Surface Signals

URL patterns to watch:

  • /checkout, /order, /subscribe, /payment, /verify, /confirm, /callback
  • /internal, /employee, /summit, /staff, /admin — internal pages accidentally public
  • /api/v*/payment, /api/v*/notify, /webhook — payment provider callbacks
  • Endpoints accepting X-Forwarded-For, X-Real-IP, CF-Connecting-IP headers

Response/header signals:

  • Set-Cookie with unvalidated session state tied to cart or order data
  • Payment provider names in responses: Smart2Pay, Stripe, PayPal, Braintree
  • Redirect chains through third-party payment pages (in-flight data opportunity)
  • 200 OK on subscription/verification endpoints with no CAPTCHA or token

JS patterns:

  • Hardcoded internal URLs in frontend bundles (/employee/, /staff/, /internal/)
  • Client-side price calculation before server submission
  • Verification logic that only checks on the frontend (if (verified) { ... })
  • fetch('/api/subscribe', { method: 'POST', body: ... }) with no anti-CSRF token or rate-limit token

Read the full file on GitHub · 199 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 199 lines · 31 tokens per session scan A 2a8022e84ffb

Subscribe to this mod's changes

hunt-business-logic is a skill published in the GitHub repository adriannoes/awesome-agentic-ai (57 stars, last pushed 14d ago), licensed MIT. It adds 31 tokens to every session and 3,022 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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