跳到正文
cccskills
免费在 GitHub 公开

auditing-foundry-smart-contract-security

Audit Solidity contracts in Foundry projects before deployment using code analysis, randomized tests, manual review, and private key checks. Produces a JSON report with findings, remediation, test coverage, and a pass or fail deployment decision.

中文简介正在准备中。当前显示英语简介。

原文查看原文说明

Pre-deployment security audit of Solidity smart contracts in a Foundry project. Combines static analysis (Slither, Aderyn), symbolic execution (Mythril), and property-based testing (forge fuzz + invariant tests with handlers) to catch reentrancy, access-control, oracle/price manipulation, and arithmetic bugs BEFORE deploying to an EVM chain. Also enforces key hygiene (no plaintext private keys, encrypted cast keystore) and a secure deploy workflow. Use when writing, reviewing, testing, or deploying Solidity/Foundry contracts, building a dApp, or working with forge/cast/anvil, MetaMask, or Web3/DeFi code.

查看安装方法

适用场景

  • Auditing Solidity contracts before deployment
  • Adding fuzz and invariant tests for contracts that move funds
  • Reviewing private key storage and deployment scripts
  • Triaging Slither and Aderyn findings

包含的文件(6)

  • SKILL.md7.4 KB
  • LICENSE11.0 KB
  • references/api-reference.md6.4 KB
  • references/secure-deployment-and-keys.md4.1 KB
  • references/vulnerability-checklist.md4.8 KB
  • scripts/agent.py13.5 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Auditing Foundry Smart Contract Security

Overview

Deployed smart contracts are immutable and custody real funds, so a bug shipped to mainnet cannot be patched — it can only be exploited. Most catastrophic DeFi losses come from a small set of recurring classes: reentrancy, broken access control, oracle/price manipulation, and unchecked arithmetic or external calls.

This skill runs a defense-in-depth, pre-deployment audit of a Foundry project, layering four independent techniques that each catch what the others miss:

  1. Static analysis — slither (90+ detectors) and aderyn (Cyfrin, Rust) scan the AST/IR in seconds for known anti-patterns.
  2. Symbolic execution — mythril (optional, slow) explores execution paths and SMT-solves for deep arithmetic/reentrancy bugs.
  3. Property-based testing — forge test with fuzzing (testFuzz_*) and invariant tests (invariant_* + handler contracts with ghost variables) proves protocol-level properties hold across millions of random sequences.
  4. Manual review + key hygiene — a structured checklist (see references/vulnerability-checklist.md) and a secrets/keystore audit so no private key ever lives in plaintext and deployment goes through an encrypted cast keystore (see references/secure-deployment-and-keys.md).

The skill is dev-side and pre-deployment — it is run by the engineer building the contract, not by a SOC after an incident. Findings gate the deploy: any high/critical static finding, failing test, leaked key, or low coverage = FAIL.

When to Use

  • Before deploying any Solidity contract to a testnet or mainnet EVM chain.
  • When writing or reviewing a Foundry project (foundry.toml, src/, test/, script/).
  • When a contract handles value: tokens (ERC-20/721/1155), vaults, staking, AMMs, bridges, governance.
  • When adding fuzz or invariant tests, or when coverage of value-moving functions is unknown.
  • When wiring deployment scripts — to verify keys are in an encrypted keystore, not .env plaintext.
  • When integrating a price oracle, external call, delegatecall, or upgradeable proxy.
  • When triaging a Slither/Aderyn report and needing to separate real bugs from false positives.

Prerequisites

  • Foundry installed (forge, cast, anvil): curl -L https://foundry.paradigm.xyz | bash && foundryup
  • Slither + solc: pip install slither-analyzer and solc-select install <ver> && solc-select use <ver>
  • Aderyn (recommended): cargo install aderyn (or npm i -g @cyfrin/aderyn)
  • Mythril (optional, slow symbolic exec): pip install mythril
  • gitleaks (key-leak scan): see the companion implementing-secret-scanning-with-gitleaks skill
  • A Foundry project that compiles (forge build succeeds) — analyzers need build artifacts.
  • Solidity ^0.8.x is assumed (built-in overflow checks); pre-0.8 contracts need extra SafeMath review.

Install the Python tools in a virtualenv (recommended on externally-managed distros). Never run analysis against untrusted contract source on a machine with funded wallets unlocked.

Steps

Step 1: Build and sanity-check the project

forge build                    # analyzers require fresh artifacts
forge fmt --check              # style gate (optional)
cat foundry.toml               # note solc version, optimizer, remappings, evm_version

Step 2: Static analysis (fast, run every time)

# Slither — full project (uses foundry.toml + remappings automatically)
slither . --json slither-report.json

# Aderyn — Cyfrin Rust analyzer, complementary detectors
aderyn . -o aderyn-report.json

Or run the bundled orchestrator that runs both, deduplicates, and gates the result:

python3 scripts/agent.py --project . --output audit-report.json

Step 3: Symbolic execution on critical contracts (optional, slow)

# Only on the highest-value contract(s) — Mythril is path-explosive
myth analyze src/Vault.sol --solc-json mythril.config.json --execution-timeout 300 -o json
# or: python3 scripts/agent.py --project . --mythril src/Vault.sol

Step 4: Property-based testing — fuzz + invariants

forge test -vvv                                  # unit + fuzz tests
forge coverage --report summary                  # coverage of value-moving code
forge test --match-test invariant_ -vvv          # invariant suite (handler-based)

Every value-moving contract should have invariant tests with a handler (bounded inputs, ghost variables, targetContract(handler)) — not just unit tests. See references/api-reference.md for the handler pattern, and write a test_RevertWhen_* (with vm.expectRevert) for each access-control guard.

Step 5: Manual review against the checklist

Walk references/vulnerability-checklist.md for every contract: reentrancy (checks-effects-interactions / nonReentrant), access control, oracle manipulation, delegatecall/proxy storage layout, unchecked return values, tx.origin, weak randomness, DoS, front-running/MEV, and ERC-specific pitfalls (approve race, fee-on-transfer, rebasing).

Step 6: Key hygiene & secure deploy

gitleaks detect --no-banner            # no private keys / mnemonics / .env committed
git ls-files | grep -E '\.env$|keystore' && echo "WARN: secrets tracked by git"

# Import the deploy key ONCE into an encrypted keystore — never a plaintext PRIVATE_KEY env
cast wallet import deployer --interactive

# Deploy via the keystore account (testnet first), simulate before --broadcast
forge script script/Deploy.s.sol --account deployer --rpc-url <testnet> --broadcast --verify

See references/secure-deployment-and-keys.md for the full hardening rules (MetaMask hygiene, hardware wallet for mainnet, RPC trust, post-deploy verification).

Step 7: Triage and report

Combine Slither + Aderyn + Mythril + test results, deduplicate by (file, line), drop confirmed false positives, rank by exploitability × financial impact, and map each to its SWC id. The orchestrator emits audit-report.json with a PASS/FAIL gate.

Expected Output

A JSON audit report listing findings with SWC identifiers, severity, tool source, affected contract/function/line, and remediation; plus the test/coverage summary and a single PASS / FAIL deploy gate. FAIL on any high/critical static finding, failing test, leaked secret, or coverage below the configured threshold on value-moving code.

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Analyze Solidity smart contracts with Slither and Mythril before Ethereum deployment. Combine code inspection with execution path analysis, review potential vulnerabilities, remove duplicate findings, and produce an audit report with severity ratings and suggested fixes.

中文简介正在准备中。当前显示英语简介。

  • Checking Solidity contracts before deployment
  • Investigating reentrancy and access control weaknesses
  • Consolidating findings from Slither and Mythril
tradecatlabs/vibe-coding-cn1.8万2026年10月19日 更新

Build reusable Claude Skills from documentation, APIs, code, and specifications. Organize instructions and reference files, define clear activation conditions, add reproducible examples, and check new or existing skills against a delivery checklist.

中文简介正在准备中。当前显示英语简介。

  • Creating a skill from documentation, code, or specifications
  • Reorganizing an overly long SKILL.md
  • Clarifying when a skill should activate
tradecatlabs/vibe-coding-cn1.8万2026年10月19日 更新

auto-tmux

免费

Automate tmux, a tool for managing multiple terminal workspaces, to inspect output, send commands, monitor stalled tasks, and record logs. Coordinate multiple AI terminals with task queues, file locks, status tracking, and handoff reports.

中文简介正在准备中。当前显示英语简介。

  • Inspect output and errors across multiple AI terminals
  • Resume tasks waiting for confirmation
  • Coordinate tasks and file locks across AI workers
tradecatlabs/vibe-coding-cn1.8万2026年10月19日 更新

Check mathematical expressions, solve equations, and search bounded ranges for counterexamples using symbolic and numerical libraries. Record assumptions, commands, and results so calculations can be repeated, while keeping computational evidence distinct from general mathematical proof.

中文简介正在准备中。当前显示英语简介。

  • Checking identities and integrals with exact arithmetic
  • Searching a defined range for counterexamples
  • Cross-checking numerical results at higher precision
tradecatlabs/vibe-coding-cn1.8万2026年10月19日 更新

Turn scattered formulas and theory notes into a derivation that can be checked step by step. Keep definitions and assumptions consistent, distinguish exact identities from approximations, and make hidden conditions and limits explicit.

中文简介正在准备中。当前显示英语简介。

  • Organize scattered formulas and theory notes
  • Trace the steps behind an algebraic identity
  • State conditions and error orders for approximations
tradecatlabs/vibe-coding-cn1.8万2026年10月19日 更新

Shape broad mathematical interests into precise research questions. Search prior work on definitions and theorems, record traceable sources, map supporting and conflicting evidence, and identify gaps that could lead to testable conjectures.

中文简介正在准备中。当前显示英语简介。

  • Tracing a theorem’s variants and related work
  • Checking prior work on an integer sequence
  • Defining search terms and the scope of a research question
tradecatlabs/vibe-coding-cn1.8万2026年10月19日 更新

查看 tradecatlabs 的全部技能

报告此技能的问题