web3-case-study-role-misconfig

web3-case-study-role-misconfig is a skill for Claude Code, Codex from Awarexone/web3-bug-bounty-hunting-ai-skills. It costs 40 tokens per session (3,319 once invoked), scanned A, original, MIT.

A worked example of looking for access-control mistakes in a yield aggregator, a service that moves deposited assets between investment protocols to seek returns. It applies a ten-category security review method to one protocol.

In plain words
What is it for?
Use it as a template for reviewing smart contracts for role or permission errors. It helps map the protocol, trace how funds move, and prioritize possible findings.
Why use it?
It gives auditors a concrete way to examine who can call important contract functions and what those permissions can change. It also shows how to judge whether a target is worth reviewing.

Skill for Claude CodeCodex

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

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is grep -r "bytes32 public constant.*ROLE" ./src/.

Good fit Use it as a template for reviewing smart contracts for role or permission errors. It helps map the protocol, trace how funds move, and prioritize possible findings.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/Awarexone/web3-bug-bounty-hunting-ai-skills
agentmods
npx agentmods add skills/awarexone/web3-bug-bounty-hunting-ai-skills/web3-case-study-role-misconfig

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 web3-case-study-role-misconfig

README.md
[![agentmods](https://agentmods.dev/badge/skills/awarexone/web3-bug-bounty-hunting-ai-skills/web3-case-study-role-misconfig/github.svg)](https://agentmods.dev/skills/awarexone/web3-bug-bounty-hunting-ai-skills/web3-case-study-role-misconfig)
Your own site
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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.

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Your own site · 80×15
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Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,319 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
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 $0.00040 $0.03319
Opus 5 $0.00020 $0.01659
Sonnet 5 $0.00008 $0.00664
Haiku 4.5 $0.00004 $0.00332

Measured 12d ago against content hash b08494af64ce, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

web3-case-study-role-misconfig scanned grade A with 0 findings 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 12d 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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

web3-case-study-role-misconfig/SKILL.md · 344 lines

How it starts

The opening of the file, as written. The whole thing — 344 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CASE STUDY: ROLE MISCONFIGURATION IN A YIELD AGGREGATOR

Bug Class: Access Control | Severity: Critical/Medium | Payout Range: $10K–$50K This file shows how to apply the full 10-class methodology to a real yield aggregator target.


TARGET PROFILE (Anonymized)

Field Value
Protocol Type Yield aggregator — stablecoin → lending protocol → harvest → DEX → reward token
Max Bounty $50K (Critical)
TVL Low (fresh program, under $100K)
Core Contracts Vault.sol, RewardsDistributor.sol
Program Age ~5 days when hunted (fresh = low competition)
Prior Audits Firm A (16 findings, all Risk Accepted) + Firm B (18 findings, all Risk Accepted)

Scorecard: Max bounty (+2) + custom math (+1) + recent code (+1) + known prior audits (+1) + public source (+1) + program new (+2) = 8/10 → HUNT

Why this scores high: Fresh program on a live bounty platform + prior audits that accepted all risk = team is aware of issues but hasn't patched them. Hunt for what auditors missed or flagged but accepted.


ARCHITECTURE + FUND FLOW

User deposits Stablecoin
    ↓ deposit(uint256 amount)
Vault.sol stores:
  - deposits[user] += amount
  - totalDeposited += amount
  - depositTimestamp[user] = block.timestamp
    ↓ safeTransferFrom(user, address(this), amount)
    ↓ lendingProtocol.supply(stablecoin, amount, address(this), 0)
  Interest-bearing token accrues in Vault.sol balance
    ↓ (periodic) _performHarvest()
  aToken balance > totalDeposited + DUST_THRESHOLD
    ↓ lendingProtocol.withdraw(stablecoin, harvestAmount - 1, address(this))
    ↓ dex.exactInputSingle(stablecoin → rewardToken)
    ↓ RewardsDistributor.distribute(rewardToken, amount)
  RewardsDistributor tracks:
  - cumulativeRewardPerShare updates
  - users can call claimFor(user) to collect rewardToken

User withdraws:
    ↓ withdraw(uint256 amount)
  if block.timestamp < depositTimestamp[user] + LOCK_PERIOD:
    withdrawFee applies (e.g. 0.5%)
  lendingProtocol.withdraw(stablecoin, amount, user)

Read the full file on GitHub · 344 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. 12d ago First seen · 344 lines · 40 tokens per session scan A b08494af64ce

Subscribe to this mod's changes

web3-case-study-role-misconfig is a skill published in the GitHub repository Awarexone/web3-bug-bounty-hunting-ai-skills (143 stars, last pushed 18d ago), licensed MIT. It adds 40 tokens to every session and 3,319 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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