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安全赏金猎人

在仓库中寻找可被利用、值得获取赏金的安全问题。专注于远程可触及的漏洞,这些漏洞符合实际报告标准,而非仅本地可见的问题。在寻找可报告、远程可触及的漏洞时使用。

安全赏金猎人 是什么?

此技能旨在帮助开发者或安全研究人员高效识别并提交具有实际利用价值的漏洞,以进行负责任披露或参与赏金计划(如 Huntr、HackerOne)。与一般的代码审查不同,它专注于远程可利用的攻击路径,并过滤掉那些通常被平台视为信息性、范围外或噪音过大的发现。技能的核心工作原理是基于一套经过验证的漏洞模式(如 SSRF、认证绕过、SQL 注入等)进行扫描,并强调对代码路径的端到端审查,以确保用户控制的输入能够到达有意义的“接收器”(如执行点、敏感函数)。它还提供了一个完整的工作流,包括范围检查、入口点发现、静态工具辅助、手动代码审计、概念验证(PoC)构建以及重复检查。该技能适用于 Claude Code、Cursor、Codex 等 AI 编码助手,通过清晰的指令和结构化输出,引导安全研究人员从理论分析转向实际的漏洞利用验证和报告撰写。

兼容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/security-bounty-hunter

在你喜欢的 AI 中提问

打开一个已预加载此 Agent Skill 的新对话。

文档

安全赏金猎人 是做什么的?

当目标是进行实际漏洞发现以用于负责任披露或赏金提交,而非进行广泛的“最佳实践”审查时,使用此技能。

何时使用

  • 扫描仓库以寻找可利用漏洞
  • 准备提交给 Huntr、HackerOne 或类似的赏金计划
  • 判断“这个问题实际能带来赏金吗?”而非“理论上它是否不安全?”的甄别过程

工作方式

偏向于寻找远程可及的、用户控制的攻击路径,并丢弃那些平台通常拒绝接受(作为信息性内容或超出范围)的模式。

范围内的模式

以下是持续重要的几种问题:

模式CWE典型影响
通过用户控制的 URL 实现的 SSRFCWE-918内部网络访问、云元数据窃取
中间件或 API 守卫中的认证绕过CWE-287未授权账户或数据访问
远程反序列化或上传到 RCE 的路径CWE-502代码执行
可达端点中的 SQL 注入CWE-89数据泄露、认证绕过、数据破坏
请求处理程序中的命令注入CWE-78代码执行
文件服务路径中的路径遍历CWE-22任意文件读取或写入
自动触发的 XSSCWE-79会话窃取、管理员账户劫持

跳过这些

除非赏金计划另有规定,以下通常信号微弱或不在赏金范围:

  • 仅本地的 pickle.loads、torch.load 或没有远程路径的等效操作
  • 仅限 CLI 工具中的 eval() 或 exec()
  • 在完全硬编码的命令中使用 shell=True
  • 单独缺失安全标头
  • 无利用影响的通用速率限制投诉
  • 需要受害者手动粘贴代码的自 XSS
  • 非目标程序范围内的 CI/CD 注入
  • 演示、示例或仅测试代码

工作流程

  1. 首先检查范围:程序规则、SECURITY.md、披露渠道和排除项。
  2. 寻找真实入口点:HTTP 处理程序、上传功能、后台任务、Webhook、解析器和集成端点。
  3. 在有用的情况下运行静态工具,但只将其视为初步筛选输入。
  4. 从头到尾阅读实际代码路径。
  5. 证明用户控制能达到一个有意义的接收器。
  6. 使用尽可能小且安全的概念验证(PoC)确认可利用性和影响。
  7. 在起草报告前检查是否有重复。

示例甄别循环

semgrep --config=auto --severity=ERROR --severity=WARNING --json

然后手动过滤:

  • 排除测试、演示、固定代码、供应商代码
  • 排除仅本地或不可达路径
  • 只保留具有清晰网络或用户控制路由的发现

报告结构

## 描述
[漏洞是什么以及为什么重要]

## 易受攻击代码
[文件路径、行范围及代码片段]

## 概念验证
[最小可运行请求或脚本]

## 影响
[攻击者能够实现什么]

## 受影响版本
[测试过的版本、提交或部署目标]

质量检查

在提交前:

  • 代码路径是从真实用户或网络边界可达的
  • 输入是真正的用户控制
  • 接收器有意义且可利用
  • 概念验证有效
  • 问题尚未被任何公告、CVE 或公开工单覆盖
  • 目标确实在赏金计划范围内

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

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