Communitygithub.com

資安漏洞獵人

在儲存庫中搜尋可被利用、符合懸賞標準的資安漏洞。專注於可遠端觸發的漏洞,而非僅存在於本機的雜訊問題。適用於尋找可提交報告、可遠端利用的漏洞。

資安漏洞獵人 是什麼?

Security Bounty Hunter 是一項專為開發者與資安研究人員設計的 AI 助手技能,旨在高效挖掘儲存庫中真正具備報告價值、可於遠端觸發的資安漏洞。其主要用途是支援負責揭露或懸賞提交流程,避免浪費時間於低訊噪或超出範圍的弱點。這項技能支援多種平台,包括 Huntr、HackerOne 等常見漏洞獎勵計畫。其運作方式強調優先關注遠端可達、使用者可控的攻擊路徑,並自動濾除平台通常會標記為資訊性、示範性或超出範圍的模式。技能提供明確的掃描流程,包括先確認計畫規則與範圍、找出真實進入點、執行靜態分析工具(如 Semgrep)作為初步篩選,再手動驗證完整程式碼路徑,最終以最小可行概念驗證(PoC)驗證可利用性與影響。同時,它也提供一份常見的低訊噪模式列表(如僅限本機的 pickle 反序列化、CLI 工具中的 eval()、硬編碼命令中的 shell=True 等),幫助使用者避免撰寫無效報告。這項技能對於任何想要快速、有效率地在開源專案或目標應用程式中識別出真正可利用漏洞並提交高品質懸賞報告的研究人員來說,極具實用性。

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

在你喜歡的 AI 中提問

開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

資安漏洞獵人 是做什麼的?

當目標是進行實用的漏洞發現,以利於負責任揭露或提交漏洞獎勵時使用,而非廣泛的最佳實務審查。

使用時機

  • 掃描儲存庫以尋找可被利用的漏洞
  • 準備提交給 Huntr、HackerOne 或類似漏洞獎勵平台的報告
  • 進行事件分級,判斷重點在於「這真的能獲得獎金嗎?」而非「這在理論上不安全嗎?」

運作方式

傾向於尋找遠端可達、使用者可控的攻擊路徑,並丟棄那些平台通常會標記為「資訊性」或「超出範圍」的模式。

範圍內模式

以下是持續具有重要性的問題類型:

模式CWE典型影響
透過使用者可控的 URL 造成的 SSRFCWE-918內部網路存取、雲端中繼資料竊取
中介軟體或 API 防護中的身分驗證繞過CWE-287未經授權的帳戶或資料存取
遠端反序列化或上傳至 RCE 路徑CWE-502程式碼執行
可達端點中的 SQL 注入CWE-89資料外洩、身分驗證繞過、資料破壞
請求處理器中的命令注入CWE-78程式碼執行
檔案服務路徑中的路徑遍歷CWE-22任意檔案讀取或寫入
自動觸發的 XSSCWE-79會話竊取、管理員帳戶被入侵

跳過這些

除非漏洞獎勵計畫另有規定,這些通常屬於低訊噪或超出懸賞範圍的項目:

  • 僅限本機的 pickle.loads、torch.load 或類似功能,且無遠端路徑
  • CLI 工具中的 eval() 或 exec()
  • 完全硬編碼命令上的 shell=True
  • 僅缺少安全性標頭
  • 不具利用影響的一般性速率限制問題
  • 需要受害者手動貼上程式碼的自我型 XSS
  • 不屬於目標計畫範圍的 CI/CD 注入
  • 示範、範例或僅供測試的程式碼

工作流程

  1. 首先確認範圍:計畫規則、SECURITY.md、揭露管道及排除項目。
  2. 找出真實進入點:HTTP 處理器、上傳功能、背景任務、Webhook、解析器及整合端點。
  3. 在有用之處執行靜態工具,但僅將其視為分級輸入。
  4. 從頭到尾閱讀真實的程式碼路徑。
  5. 證明使用者控制能抵達有意義的接收器。
  6. 以最小的安全概念驗證 (PoC) 確認可利用性與影響。
  7. 在撰寫報告前檢查是否與現有報告重複。

範例分級迴圈

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

然後手動篩選:

  • 移除測試、示範、測試用固定程式碼、供應商程式碼
  • 移除僅限本機或不可達的路徑
  • 僅保留具有明確網路或使用者控制路由的發現

報告結構

## 描述
[漏洞是什麼以及為何重要]

## 有漏洞的程式碼
[檔案路徑、行數範圍以及一小段程式碼]

## 概念驗證
[最小可行的請求或腳本]

## 影響
[攻擊者可以達成什麼]

## 受影響版本
[測試時的版本、提交或部署目標]

品質閘門

提交前:

  • 程式碼路徑可從真實使用者或網路邊界觸及
  • 輸入確實由使用者控制
  • 接收器有意義且可被利用
  • PoC 可行
  • 該問題尚未被公告、CVE 或已開啟的工單涵蓋
  • 目標實際上在漏洞獎勵計畫的範圍內

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.

相關技能