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Anti Rug

Name: Anti Rug
Author: deanpeng-dotcom

作者 deanpeng-dotcom · GitHub ↗ · v3.1.0 · MIT-0

cross-platform ✓ 安全检测通过

102

总下载

当前安装

版本数

在 OpenClaw 中安装

/install anti-rug

功能描述

Web3 token security scanner with expert cross-validation engine. Detects honeypots, rug pulls, and contract risks across Ethereum, BSC, Polygon, and other EV...

使用说明 (SKILL.md)

Web3 Token Security Scanner (Anti-Rug)

Maintainer: Antalpha AI Team

A professional-grade token contract security analyzer featuring scenario-based classification and cross-validation engine.

Overview

This tool performs comprehensive security analysis of token contracts with:

Scenario Classification: Automatically categorizes tokens (A: Pegged Assets, B: Eco Tokens, C: Meme Coins)
Cross-Validation Engine: Analyzes relationships between indicators (neutralized/amplified/contextual)
Dynamic Risk Scoring: Weighted scoring system adapted to token type
Fatal Finding Detection: One-strike rules for critical vulnerabilities

Supported Chains

Ethereum (chain_id: 1)
BNB Smart Chain (chain_id: 56)
Polygon (chain_id: 137)
Arbitrum One (chain_id: 42161)
Base (chain_id: 8453)
Optimism (chain_id: 10)
Avalanche C-Chain (chain_id: 43114)
Solana (chain_id: solana)

Installation

git clone https://github.com/ZorroShao/anti-rug.git
cd anti-rug
pip install -r requirements.txt

Usage

python scripts/check_token.py --chain_id 56 --contract_address 0x...

Scenario Classification

Scenario A: Pegged/Stable Assets

Examples: USDT, USDC, WETH, WBNB

Mintable: ✅ Expected for peg maintenance
Owner: ✅ Institution custody is normal
Blacklist: ✅ Compliance requirement

Scenario B: Ecosystem Tokens

Examples: UNI, AAVE, established DeFi

Proxy: ✅ Acceptable for upgradeability
Treasury: ✅ Protocol-owned liquidity expected

Scenario C: Meme/Unknown Tokens

All permissions: ⚠️ Treated as potential rug tools
Strictest evaluation applied

Risk Severity Levels

Score	Level	Action
0-24	Low	✅ Base security passed
25-49	Low-Medium	🟡 Minor concerns
50-74	Medium	🟡 Caution required
75-100	High	🔴 Dangerous
Fatal	Critical	🛑 Do not buy

Architecture

config.py           # Centralized configuration
exceptions.py       # Custom exception classes
validators/         # Cross-validation rules (modular)
  cv_mint_ownership.py
  cv_concentration.py
  cv_proxy.py
  cv_tax_scenario.py
tests/              # Unit tests
scripts/
  check_token.py    # Main entry point

License

MIT License - See LICENSE file

安全使用建议

This package appears to do what it says: it queries a token‑security API (api.gopluslabs.io) for indicators, runs local validators, and reports risks. Before installing or running it: 1) be aware that contract addresses you check are sent to the external API (and to any custom --api_gateway you provide); do not point --api_gateway at untrusted services. 2) There is a minor inconsistency between repo URLs in SKILL.md vs README (ZorroShao vs AntalphaAI) — consider verifying the upstream source/maintainer on GitHub. 3) The config stores runtime lambda check functions (FATAL_RULES) — these are executable Python objects (normal here but harder to audit if persisted/serialized). 4) If you want to be extra cautious, run the tool in an isolated environment, review the GoPlus endpoint privacy/terms, and run the included tests (pytest) locally. Overall the skill is internally coherent with no disproportionate credential or install demands.

功能分析

Type: OpenClaw Skill Name: anti-rug Version: 3.1.0 The Anti-Rug skill bundle is a well-structured Web3 security tool designed to analyze token contracts for risks like honeypots and rug pulls. It uses the legitimate GoPlus API (api.gopluslabs.io) to fetch contract data and implements a modular cross-validation engine to calculate risk scores. No evidence of data exfiltration, malicious execution, or prompt injection was found; the code logic is consistent with its stated purpose.

能力标签

crypto

能力评估

✓ Purpose & Capability

Name/description align with the included Python code and validators. The repo contains a CLI script that fetches token data, runs validators, and computes scores — all appropriate for a token security scanner. No unrelated credentials, binaries, or system‑level access are requested.

ℹ Instruction Scope

Runtime instructions and the code perform outbound HTTP requests to third‑party endpoints (api.gopluslabs.io) carrying the chain_id and contract_address — this is expected to fetch token indicators, but it does transmit the contract addresses to an external service. The CLI also accepts a --api_gateway argument allowing use of a custom proxy; that is useful but means a malicious gateway could receive query data if supplied.

✓ Install Mechanism

No registry install spec was provided, but SKILL.md documents a normal git + pip workflow and requirements.txt only lists 'requests' (and typing-extensions for older Python). There are no downloads from personal servers, IP addresses, or archive extraction steps in the package metadata.

✓ Credentials

The skill does not declare or require any environment variables, credentials, or config paths. It operates with provided CLI args and uses public API endpoints — no secret access is requested or implied.

✓ Persistence & Privilege

always is false and the skill does not modify other skills or system settings. It does allow autonomous invocation (disable-model-invocation=false) which is the platform default; this is not a red flag on its own and is not combined with broad privileges.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install anti-rug
安装完成后，直接呼叫该 Skill 的名称或使用 /anti-rug 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v3.1.0

- Added support for Solana chain alongside EVM chains (Ethereum, BSC, Polygon, etc.). - Introduced a scenario-based classification system for tokens (Pegged Assets, Ecosystem Tokens, Meme/Unknown Tokens). - Implemented a cross-validation engine analyzing the relationship between risk indicators. - Updated risk scoring and severity levels, including fatal finding detection for critical vulnerabilities. - Expanded and clarified documentation, installation, and usage instructions.

元数据

Slug anti-rug

版本 3.1.0

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 1

常见问题

Anti Rug 是什么？

Web3 token security scanner with expert cross-validation engine. Detects honeypots, rug pulls, and contract risks across Ethereum, BSC, Polygon, and other EV... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 102 次。

如何安装 Anti Rug？

在 OpenClaw 或 Claude Code 对话框中运行命令「/install anti-rug」即可一键安装，无需额外配置。

Anti Rug 是免费的吗？

是的，Anti Rug 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。

Anti Rug 支持哪些平台？

Anti Rug 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。

谁开发了 Anti Rug？

由 deanpeng-dotcom（@deanpeng-dotcom）开发并维护，当前版本 v3.1.0。