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Web3 Hunt Foundation

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tradecatlabs
web3-hunt-foundation

Hunter mindset, recon setup, and target scoring for Web3 bug bounty. Use at the START of any new protocol hunt - scoring targets, setting up environment, understanding architecture.

Overview

Publishertradecatlabs
Repositoryvibe-coding-cn
Skill nameweb3-hunt-foundation
Stars
16.3K
Forks
1.6K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by tradecatlabs on GitHub. Read the source before you install it.

Installation

Install the Web3 Hunt Foundation AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/tradecatlabs/vibe-coding-cn.git /tmp/vibe-coding-cn
mkdir -p .claude/skills
cp -r /tmp/vibe-coding-cn/research/vibe-cybersecurity-cn/skills/web3-bug-bounty-hunting/web3-hunt-foundation .claude/skills/web3-hunt-foundation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Web3 Hunt Foundation in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Web3 Hunt Foundation on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Web3 Hunt Foundation is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

WEB3 HUNT FOUNDATION

Mindset + Recon + Setup. Read this before touching any new target's code. Replaces: 01-mindset, 02-recon-setup, 20-chain-complete


PART 1: THE HUNTER MINDSET

The Core Mental Shift

You are NOT looking for "vulnerabilities" in the abstract. You are looking for specific actions an attacker can take TODAY that result in profit.

Everything flows from one question: "What can I STEAL, FREEZE, or DESTROY — and what do I END UP WITH?"

The Bug Validation Template

Apply to every finding before writing a single line:

I am an attacker. I will:
1. SETUP:   What do I need? (wallet, capital, any whitelisted permissions?)
2. CALL:    Exact transactions, exact order, exact function names
3. RESULT:  What do I end up with that I didn't start with?
4. COST:    Gas + capital + flash loan fee + any other expense
5. DETECT:  Can anyone stop or reverse this?
6. NET ROI: I gained X at cost of Y. Is Y << X?

If you can't fill in steps 2 and 3 with specific function calls → it's not a real bug. Stop. Move on.

10 Attacker Questions (Ask For Every External Function)

  1. What if amount = 0? Does anything revert or silently pass?
  2. What if I call this function twice in the same block?
  3. What if I call this before initialize() is called?
  4. What if I front-run this transaction?
  5. What if the external call fails? Does state get half-updated?
  6. What if the token has fee-on-transfer? Does amount received ≠ amount sent?
  7. What if I pass address(0) or a malicious contract as an address param?
  8. What if I pass type(uint256).max as a numeric param?
  9. Can I combine this with a flash loan? (zero-cost capital changes the math)
  10. Does a sibling function lack the same modifier this function has?

Question #10 explains 19% of all Critical findings. If vote() has onlyRole(VOTER), check poke(), reset(), harvest() — the missing modifier on the sibling IS the bug.

6 Triager Counter-Questions (Disprove Your Own Finding)

Before spending time on a PoC, try to KILL the finding:

  1. Is there an upstream check I missed that actually prevents this?
  2. Is this documented intended behavior (whitepaper, NatSpec, design decision)?
  3. Does exploitation require admin/privileged access? (Usually invalid if yes)
  4. Is the economic cost to exploit greater than the gain? (Not viable if yes)
  5. Was this flagged in a prior audit as "acknowledged" or "risk accepted"?
  6. Is the "sensitive" data already publicly visible to anyone in the web UI?

One YES = KILL. Move on.

5-Minute Rule

If you've been on the same function for 5 minutes with no clear attack path → STOP. Add it to a low-priority list. Move to the next function. Top hunters: 95% fast-reject + 5% deep dives on confirmed leads.

Depth Over Breadth

Don't review 10 protocols in one week. Pick ONE. Spend 3-5 days becoming the expert. Protocol-specific knowledge compounds. The Curve expert found 5 bugs. The 10-protocol tourist found 0.

Inconsistency Is Proof

If functionA() has a security check, and functionB() doesn't — that IS the report. You don't need to fully understand why. The inconsistency proves the developer intended the check.


PART 2: TARGET SCORING — GO / NO-GO

Before touching any code: score the target. Score < 6 → skip.

Target Scorecard

CriterionPointsHow to Check
Max bounty ≥ $50K+2Immunefi program page
TVL > $1M+2DeFiLlama
Program launched < 30 days ago+2Immunefi "new" filter
Custom math (AMM/vault/lending)+1Read scope contracts
Recent code changes+1git log --oneline -20
Prior audits available+1Program page / GitHub
In-scope includes smart contracts+1Scope section
Protocol type you know well+1Your specialization
Source code public/readable+1GitHub / Etherscan verified

< 4: Skip — too small, too audited, wrong fit 4-5: Only if nothing better available 6-8: Good — spend 1-3 days ≥ 9: Excellent — spend up to 1 week


PART 3: RECON METHODOLOGY (30-Minute Protocol)

Step 1 — Read Immunefi Page (5 min)

Note:
- All in-scope contract addresses + GitHub links
- Out-of-scope list (DO NOT report these)
- Primacy of Impact: YES/NO (YES = more forgiving on novel impacts)
- Max bounty amounts by severity
- Time on Immunefi (newer = fewer duplicates)

Step 2 — Clone + Setup (5 min)

bash
git clone <target-repo>
cd <target-repo>
git log --oneline -20       # Recent changes = freshest bugs here
forge build                 # Must compile clean (fix if not)
forge test                  # Note failures — may indicate known issues
forge coverage              # Untested code = priority review target

Step 3 — Read ALL Prior Audit Reports (15 min)

For each finding, note its status:

  • Fixed: Skip
  • Acknowledged / Risk Accepted:START HERE
    • Developer knows about it but chose not to fix it
    • Variants, escalations, related attack paths = in-scope and uncovered
  • Partially Fixed: Verify fix actually closes ALL attack paths

Find audits: GitHub repo, protocol docs, Immunefi page, Google "[protocol] audit report"

Step 4 — Crown Jewels (2 min)

Ask: "Worst thing an attacker could do to users of this protocol?"

Work backward from impact to code:

  • "Steal deposits" → find: withdrawal functions, access control on transfer
  • "Mint infinite tokens" → find: mint functions, who calls them, what checks
  • "Freeze all funds" → find: emergency functions, time locks, role assignments
  • "Steal all rewards" → find: reward distribution, distributor role, harvest functions

Step 5 — Architecture + Fund Flow (3 min)

Draw the money flow (even mentally):

User USDC
   ↓ deposit()
[Protocol Vault] ──→ External Protocol (Aave/Compound/Uniswap)
   ↓ yield accumulates
[Reward Distributor] ──→ Users via claim/harvest

Find WHERE VALUE ACCUMULATES. That contract = highest priority.

Key state variables to map:

  • Total deposited / total assets / total shares
  • Per-user balance tracking (how is it updated?)
  • Reward accumulator (index, per-share, per-second?)
  • Role assignments (owner, admin, governance, distributor)
  • Time locks (timestamps, epochs, cooldowns)

Step 6 — Static Analysis (5 min)

bash
# Slither — 93 detectors, fast
slither . --exclude-low --filter-paths "test|lib|node_modules"
slither . --detect reentrancy-eth,unprotected-upgrade,arbitrary-send-eth

# Aderyn — Rust-based, Foundry-native
aderyn . --output report.md

# Read output → note HIGH/CRITICAL only
# Tools catch ~30-40% of bugs. Human review finds the rest.

PART 4: RECON CHECKLIST

Run through this before any deep review:

PROGRAM:
[ ] Max bounty noted per severity
[ ] ALL in-scope contracts listed (name + address)
[ ] Out-of-scope list read — nothing to falsely report
[ ] Primacy of Impact: YES/NO noted
[ ] Program launch date noted (new = good)

PRIOR AUDITS:
[ ] All audit PDFs downloaded and scanned
[ ] Each finding: status noted (Fixed/Ack/Risk Accepted)
[ ] Acknowledged items in notes as starting points

CODEBASE:
[ ] git clone + forge build passes
[ ] git log checked — recent commits noted
[ ] forge coverage run — untested functions noted
[ ] Slither + Aderyn run — high/critical noted

ARCHITECTURE:
[ ] Fund flow drawn
[ ] Crown jewels identified (where value lives)
[ ] External dependencies mapped (Chainlink, Uniswap, Aave, etc.)
[ ] ALL privileged roles found (onlyOwner, onlyRole, etc.)
[ ] Proxy/upgradeable pattern identified (if any)

ATTACK SURFACE:
[ ] All external/public non-view functions listed
[ ] Mint/burn functions located
[ ] Withdraw/emergencyWithdraw functions located
[ ] Upgrade/migration functions located
[ ] Oracle dependencies found
[ ] Signature/permit usage found
[ ] Cross-contract interactions mapped

ATTACK SURFACE BY PROTOCOL TYPE

DEX / AMM:
- Oracle manipulation (getReserves, slot0 = flash-loan manipulable)
- Rounding in pool math (1-wei attacks × flash swap)
- Missing slippage protection (sandwich vector)
- Fee-on-transfer token handling

LENDING / BORROWING:
- Collateral valuation (oracle → overborrow)
- Liquidation logic (bad debt creation, self-liquidation)
- Interest accrual rounding (favors borrower or protocol?)
- Flash loan → inflate collateral → borrow → repay

VAULT / YIELD:
- First depositor share inflation (ERC4626)
- Donation attack via direct balanceOf transfer
- Strategy rug (malicious strategy contract)
- Reward accounting timing (enter/exit attacks)

BRIDGE / CROSS-CHAIN:
- Message replay (missing nonce/nullifier)
- Signature replay (no chainId)
- Validator set manipulation
- Destination execution reentrancy

STAKING / RESTAKING:
- Reward distribution timing attacks
- Slashing logic errors
- Role never granted → permanent lock
- Withdrawal queue multi-field desync

WHEN TO RE-READ THIS CHAIN

SituationFile to Read
Starting new huntThis file
Need specific grep commands03-grep-arsenal
Found a bug, building PoC04-poc-and-foundry
Ready to validate + submit05-triage-report
Need all bug class patterns02-bug-classes
Want external research depth06-methodology
Hunting Ern protocol07-live-hunt-ern
Want AI tool automation08-ai-tools

→ NEXT: 02-bug-classes.md

Frequently asked questions

What does the Web3 Hunt Foundation AI skill do?

Hunter mindset, recon setup, and target scoring for Web3 bug bounty. Use at the START of any new protocol hunt - scoring targets, setting up environment, understanding architecture.

Why use Web3 Hunt Foundation on TypingMind?

Because you install it once and use it with any model. Web3 Hunt Foundation is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Web3 Hunt Foundation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tradecatlabs/vibe-coding-cn/tree/develop/research/vibe-cybersecurity-cn/skills/web3-bug-bounty-hunting/web3-hunt-foundation. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Web3 Hunt Foundation?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Web3 Hunt Foundation?

As many as you like. As long as a model supports skills, you can use Web3 Hunt Foundation with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Web3 Hunt Foundation AI skill free?

Yes. It is published on GitHub by tradecatlabs under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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