Borrowing it
Nothing to install: this file belongs to zhaji2333/CkSKILLS. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/zhaji2333/CkSKILLS/main/.agents/skills/auth-access-control/SKILL.mdgit clone --depth 1 https://github.com/zhaji2333/CkSKILLSWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/zhaji2333/ckskills/auth-access-control)<a href="https://agentmods.dev/skills/zhaji2333/ckskills/auth-access-control"><img src="https://agentmods.dev/badge/skills/zhaji2333/ckskills/auth-access-control.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00125 | $0.03087 |
| Opus 5 | $0.00063 | $0.01543 |
| Sonnet 5 | $0.00025 | $0.00617 |
| Haiku 4.5 | $0.00013 | $0.00309 |
Grade A, and why
auth-access-control scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
auth-access-control — 认证授权与越权专项深度挖掘
何时调用（触发条件）
- 注册/登录/找回密码/绑定换绑/实名认证/第三方登录/SSO/2FA 功能
- JWT/Token/Session 机制存在或可疑
- 发现对象ID可控（订单、用户、地址、收藏）
- 发现 role/admin/tenant_id 等参数可控
- 同一接口不同角色返回差异
- 加密/签名参数需要逆向分析（自研加密、弱哈希、可预测随机数；公网可取的 RSA/AES/uuid 当鉴权 →
unauth-path-key-hunt） - 前后端分离应用的路由守卫/前端鉴权（Vue/React 路由守卫、localStorage 登录态、前端 role 字段）
一、身份认证与会话安全
| 类型 | 场景 | 挖掘要点 |
|---|---|---|
| A1. 弱口令/默认口令 | 管理后台、运维面板、测试账号残留 | 字典策略、验证码绕过、MFA检查 |
| A2. 认证绕过 | 客户端校验、异常路径放行 | 不同header/cookie/参数组合对比 |
| A3. 会话固定/劫持 | 登录前后session不变 | Secure/HttpOnly/SameSite检查 |
| A4. JWT/Token风险 | 弱密钥、alg混淆、过期不校验 | token校验逻辑、重放测试 |
二、前端鉴权绕过 / 路由守卫绕过
适用场景：Vue / React / Angular 等前后端分离应用，前端通过
router.beforeEach、AuthGuard、本地 role 字段、localStorage/sessionStorage 中的登录态控制页面访问；服务端接口未做二次校验或校验可被绕过。
2.1 常见前端鉴权模式与绕过点
| 模式 | 绕过思路 | 验证方法 |
|---|---|---|
| 前端路由守卫（Vue Router / React Router） | 直接请求后端 API 或构造 URL 访问目标页，绕过守卫 | 拦截 /login 后的跳转，直接访问 /admin#/dashboard |
| localStorage/sessionStorage 存储登录态 | 修改/伪造 token、role、isAdmin 等字段 |
控制台 localStorage.setItem('role','admin') 后刷新 |
| 前端 role/admin 字段控制菜单/按钮 | 接口返回 role 字段，前端仅隐藏入口；直接调用后端管理接口 |
抓包改 role，观察后端是否真正校验 |
| JS 源码中硬编码角色/权限 | source map/解包后搜索 admin、role、permission |
webpack/source map 还原、Chrome Sources 定位 |
| 路由异常路径 / Hash 模式差异 | 未定义路由、404、错误分支被放行；Hash 模式 #/admin 绕过服务端路径限制 |
对比 /admin 与 /#/admin；构造 #/admin/不存在路径 观察是否放行 |
2.2 挖掘步骤
- 识别前端框架：查看 JS bundle、路由库（vue-router、react-router-dom）、构建产物（webpack、vite、umi）。
- 提取路由表：从
router.js、JS map、反编译产物中提取所有路由路径，特别是/admin、/manage、/console、/system等管理路由（JS/source map 还原详见recon-js-analysis）。 - 分析路由守卫逻辑：定位
beforeEach、onEnter、AuthGuard、PrivateRoute，确认校验依赖的是前端存储还是后端接口。 - 绕过验证：按 2.1 表格验证方法逐项执行；另测删除/篡改路由守卫 JS（Chrome Overrides、Burp 替换响应体）。
- 后端接口二次校验：即使绕过前端页面，也要测试对应 API 是否真正鉴权；前端绕过 ≠ 后端未授权，后者才是有效漏洞。
三、验证码安全专项
适用场景：注册/登录/找回密码/绑定手机/敏感操作（改密/转账/提现）前的图片、短信、邮件、滑动/点选、行为验证码。
3.1 类型特有攻击面
| 类型 | 特有攻击点 |
|---|---|
| 图片验证码 | OCR 识别、干扰弱、时效长 |
| 短信/邮件验证码 | 轰炸（对他人手机号/邮箱无限发）、4-6 位短码可爆破、与接收渠道未绑定 |
| 滑动/点选验证码 | 轨迹伪造、拦截校验接口伪造 success=true / riskLevel=0 |
| 行为验证码（无感） | 设备指纹伪造、风控阈值宽松 |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago Changed · +1 lines 411a7f886156
- 8d ago First seen · 165 lines · 125 tokens per session scan A dd1e1637b747
auth-access-control is a skill published in the GitHub repository zhaji2333/CkSKILLS (76 stars, last pushed 7d ago), licensed MIT. It adds 125 tokens to every session and 3,087 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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