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Agent Skill · 研究检索

fraud-detection(欺诈检测)

fraud-detection 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

fraud-detection 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 54,591。

总安装 504周安装 21GitHub Stars 19下载 168核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:fraud-detection(欺诈检测)
来源仓库:https://github.com/finsilabs/awesome-ecommerce-skills
仓库路径:skills/fraud-detection
安装命令:
npx skills add https://github.com/finsilabs/awesome-ecommerce-skills --skill fraud-detection
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/finsilabs/awesome-ecommerce-skills --skill fraud-detection

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。通过 npx skills add 命令从指定仓库安装,需确认权限和维护状态。使用前建议核实是否会触发联网、命令执行或文件读写操作。

fraud-detection 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/fraud-detection

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/finsilabs/awesome-ecommerce-skills --skill fra…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

fraud-detection 怎么安装?

在终端执行 npx skills add https://github.com/finsilabs/awesome-ecommerce-skills --skill fraud-detecti…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

fraud-detection 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

fraud-detection 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

fraud-detection 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

fraud-detection 用的人多吗?

公开数据是累计安装 504 次,近一周安装 21 次,下载 168 次,GitHub 19 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

fraud-detection 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
fraud-detection

欺诈检测 · 本页

50419只读未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Fraud Detection

Overview

Payment fraud costs e-commerce merchants 2–3% of revenue through chargebacks, lost goods, and dispute fees. Effective fraud detection layers platform-native risk scoring, 3D Secure authentication, velocity checks, and manual review queues for suspicious orders. The right approach depends on your platform — Shopify includes a built-in fraud analysis tool, while WooCommerce and BigCommerce require a dedicated fraud prevention service or payment processor's fraud tools.

When to Use This Skill

  • When chargeback rates exceed 0.5% of transaction volume (Visa's threshold for "excessive" disputes is 0.9%)
  • When launching in a new market with unfamiliar fraud patterns
  • When selling high-value, easily resold goods (electronics, gift cards, luxury items)
  • When you observe account takeover patterns, card testing, or bulk bot purchases
  • When building or auditing a checkout flow that processes card-not-present transactions

Core Instructions

Step 1: Determine the merchant's platform and choose the right fraud tools

PlatformBuilt-in Fraud AnalysisRecommended Fraud Service
ShopifyShopify Fraud Analysis (included free); basic risk scoring on ordersEnable Stripe Radar or Signifyd (Shopify App Store) for advanced ML scoring
WooCommerceNone built inUse Stripe (with Radar) or Braintree as payment processor; or install Kount or NoFraud plugin
BigCommercePayment processor fraud tools (varies by processor)Signifyd integrates natively with BigCommerce; NoFraud also supports BigCommerce
All platforms—Stripe Radar (if using Stripe) provides ML-based fraud scoring on every charge at no extra cost

Step 2: Enable and configure platform-native fraud tools


Shopify

Shopify includes a Fraud analysis indicator on every order based on signals like IP/billing address mismatch, card verification failure, and known fraud patterns.

Reviewing fraud indicators:

  1. Open any order in Shopify admin
  2. Click Fraud analysis in the order details panel
  3. Shopify shows a risk level (High / Medium / Low) with specific reasons (e.g., "Card verification value failed", "IP and billing address country differ")

Configuring fraud response rules:

  1. Go to Settings → Payments → Fraud prevention (if using Shopify Payments)
  2. Enable Automatic review for orders flagged as high risk — Shopify will hold these orders and send you an email
  3. Set Automatically cancel for orders Shopify deems highest risk

Signifyd (Shopify App Store — Guaranteed Fraud Protection): Signifyd provides chargeback guarantees — if they approve an order and it results in a chargeback, they reimburse you. This is the most comprehensive solution for Shopify.

  1. Install Signifyd from the Shopify App Store
  2. Signifyd automatically reviews every order using ML scoring
  3. Orders Signifyd flags go into a review queue in the Signifyd console
  4. Set up the Signifyd Shopify integration to automatically hold or cancel high-risk orders

WooCommerce

WooCommerce does not include fraud detection. You need either a payment processor with built-in fraud tools or a dedicated plugin.

Option A: Stripe Radar (recommended if using Stripe for WooCommerce)

If using the WooCommerce Stripe Payment Gateway:

  1. Stripe Radar is automatically enabled — it scores every charge on your Stripe account
  2. In the Stripe Dashboard, go to Radar → Rules to add custom blocking/review rules: # Block orders over $500 from high-fraud-rate IP countries Block if:order_amount: > 50000 and:ip_country: in ('NG', 'RO') # Review first-time customers placing large orders Review if:order_amount: > 20000 and:customer_account_age: < 7 # Block cards used more than 3 times in the last hour Block if:card_velocity_hour: > 3
  3. Orders flagged for review appear in Stripe Dashboard → Radar → Reviews

Option B: WooCommerce Anti-Fraud plugin (free)

  1. Install WooCommerce Anti-Fraud from the plugin directory
  2. Configure risk scoring rules based on:

- Order amount thresholds - New customer + high value combination - Proxy/VPN IP detection - Billing/shipping country mismatch

  1. High-risk orders are placed in "On Hold" status for manual review

Option C: Kount or NoFraud (enterprise) For high-volume WooCommerce stores, enterprise fraud prevention platforms offer:

  • Kount: full fraud management platform with ML scoring, manual review tools, and chargeback management
  • NoFraud: provides a fraud protection guarantee similar to Signifyd; integrates via WooCommerce plugin

BigCommerce

Signifyd for BigCommerce:

  1. Install the Signifyd app from the BigCommerce App Marketplace
  2. Configure automatic hold or cancellation of high-risk orders
  3. Signifyd's guarantee covers chargebacks on approved orders

Payment processor fraud tools:

  • Stripe (via BigCommerce Stripe integration): Radar is included; configure rules in the Stripe Dashboard
  • PayPal: PayPal's fraud management filters are available in your PayPal business account settings
  • Braintree: Advanced fraud protection via Kount is available as an add-on

Custom / Headless

For custom storefronts using Stripe, leverage Stripe Radar for ML scoring and add application-layer velocity checks for business-specific patterns.

Retrieve Stripe's fraud score after payment attempt:

const paymentIntent = await stripe.paymentIntents.retrieve(paymentIntentId, {
  expand: ['latest_charge'],
});
const riskScore = paymentIntent.latest_charge.outcome?.risk_score;   // 0–100
const riskLevel = paymentIntent.latest_charge.outcome?.risk_level;   // 'normal', 'elevated', 'highest'

Request 3D Secure for high-risk transactions (shifts chargeback liability to card issuer):

const paymentIntent = await stripe.paymentIntents.create({
  amount: order.totalCents,
  currency: 'usd',
  payment_method_options: {
    card: {
      // 'automatic' = Stripe decides; 'challenge' = always require 3DS for high-risk
      request_three_d_secure: riskScore > 70 ? 'challenge' : 'automatic',
    },
  },
});

Application-layer velocity checks:

import Redis from 'ioredis';
const redis = new Redis(process.env.REDIS_URL!);

async function checkVelocity(params: { email: string; ip: string; cardFingerprint: string; amountCents: number }) {
  const { email, ip, cardFingerprint, amountCents } = params;

  // IP: max 10 orders per hour
  const ipCount = await redis.incr(`vel:ip:${ip}`);
  if (ipCount === 1) await redis.expire(`vel:ip:${ip}`, 3600);
  if (ipCount > 10) return { allowed: false, reason: 'ip_velocity' };

  // Email: max 5 orders per 24 hours
  const emailCount = await redis.incr(`vel:email:${email.toLowerCase()}`);
  if (emailCount === 1) await redis.expire(`vel:email:${email.toLowerCase()}`, 86400);
  if (emailCount > 5) return { allowed: false, reason: 'email_velocity' };

  // Card: max $500 per day
  const spendKey = `vel:spend:${cardFingerprint}`;
  const currentSpend = parseInt(await redis.get(spendKey) ?? '0');
  if (currentSpend + amountCents > 50000) return { allowed: false, reason: 'daily_spend_limit' };

  return { allowed: true };
}

Manual review queue:

async function flagForManualReview(orderId: string, riskScore: number, signals: Record<string, unknown>) {
  // Hold the order — do NOT fulfill; do NOT capture payment (authorize only)
  await db.orders.update(orderId, {
    status: 'pending_fraud_review',
    fraud_risk_score: riskScore,
    fraud_signals: signals,
    review_requested_at: new Date(),
  });

  // Notify fraud review team
  await sendSlackAlert('#fraud-review', {
    text: `Order ${orderId} flagged for review. Risk score: ${riskScore}/100`,
    actions: [
      { text: 'Approve', url: `${ADMIN_URL}/fraud-review/${orderId}/approve` },
      { text: Reject', url: `${ADMIN_URL}/fraud-review/${orderId}/reject` },
    ],
  });
}

// Auto-cancel unreviewed orders after 48 hours
async function expireUnreviewedOrders() {
  const expired = await db.orders.findExpiredReviews(48);
  for (const order of expired) {
    await stripe.paymentIntents.cancel(order.payment_intent_id);
    await db.orders.update(order.id, { status: 'fraud_review_expired' });
    await sendOrderCancellationEmail(order);
  }
}

Best Practices

  • Layer defenses — no single signal reliably stops all fraud; combine Stripe Radar, velocity checks, IP reputation, and device fingerprinting
  • Use authorize-then-capture for high-risk orders — authorize at checkout to hold funds, then capture only after fraud review passes; releasing an authorization is less costly than issuing a refund
  • Track false positive rate as a KPI — if more than 1% of legitimate orders are blocked or held, your rules are too aggressive; measure both fraud losses and revenue lost to false positives
  • Rotate and obfuscate fraud rules — sophisticated fraudsters probe checkout flows to find rule thresholds; never expose block reasons in API error messages
  • Keep a deny-list of fraudulent emails, cards, and devices — once fraud is confirmed via chargeback, add the identifiers to a blocklist for future orders
  • Review your chargeback rate monthly — if it climbs above 0.5% for Visa/Mastercard, review your fraud rules; exceeding 0.9% triggers Visa's dispute monitoring program

Common Pitfalls

ProblemSolution
3DS causing checkout abandonmentUse automatic 3DS mode — Stripe decides when a challenge is needed; this frictionlessly authenticates low-risk transactions
Velocity rules blocking legitimate bulk buyersWhitelist B2B customers or high-LTV customer segments from velocity rules; use tiered limits based on account history
Manual review queue growing unboundedlySet SLA targets (4-hour review window); implement auto-cancellation for orders not reviewed within 48 hours
Chargeback filed despite 3DS authenticationVerify your processor submits 3DS authentication data (eci, cavv, xid) correctly; without these fields the liability shift does not apply
Redis velocity keys never expiringAlways call EXPIRE when setting a new key; use SET key value EX seconds NX for atomic set-if-not-exists with expiry

Related Skills

  • @secure-checkout
  • @account-security
  • @stripe-integration
  • @bot-protection
  • @gdpr-ecommerce

平台分布

Codex

35.88%
按下载量换算60

Claude

31.09%
按下载量换算52

Cursor

17.17%
按下载量换算29

Gemini CLI

8.94%
按下载量换算15

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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