find-crypto-entry

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Mis à jour12 juillet 2026 à 05:36

Internal/support tool for locating the JS source of one concrete encrypted request field, sign, x-sign, authKey, or token. Use directly only when the user explicitly asks for an atomic entry-location task such as "找加密入口", "签名怎么算", or "这个请求头字段哪里生成"; otherwise let reverse-js-crawler or website-314-api-delivery choose it. Do not trigger for generic crawler delivery, ordinary request inspection, challenge/WAF backend acceptance, or non-encrypted parameters.

Installation

Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.

Source

zy950618

zy950618/oh_my_reverse_skill

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Téléchargement

Métiers associésSOC

Basé sur la classification professionnelle SOC

Développeurs de logicielsProfessions informatiques et mathématiques·SOC 15-1252

Explorateur de fichiers

15 fichiers

SKILL.md

readonly

name	find-crypto-entry
standard_type	internal_tool
description	Internal/support tool for locating the JS source of one concrete encrypted request field, sign, x-sign, authKey, or token. Use directly only when the user explicitly asks for an atomic entry-location task such as "找加密入口", "签名怎么算", or "这个请求头字段哪里生成"; otherwise let reverse-js-crawler or website-314-api-delivery choose it. Do not trigger for generic crawler delivery, ordinary request inspection, challenge/WAF backend acceptance, or non-encrypted parameters.
argument-hint	["参数名"]
platforms	["web","h5"]

find-crypto-entry

Hardened Tool Governance

Version: 0.5.0

Change log: 0.5.0 adds structured eval coverage, graph/impact examples, and a hard delivery gate for evidence-first crypto-entry work.

Workflow:

Use references/governance.md before final output, especially when the target field affects endpoints, request headers, request body, cache state, session state, or evals.
Use references/graph-impact-examples.md when writing node/edge updates or impact-regression records.
Treat the final observed API request/response and captured call stack as the source of truth. Do not infer hidden endpoints, parameters, cookies, tokens, device IDs, signatures, or risk tokens.

Success Criteria:

Output the parameter, script URL, line/column or searchable offset, function name, call path, observed request URL, and evidence pointer.
Classify every important claim as observed, derived, assumed, or unverified.
Update 站点经验库/<domain>/knowledge-graph.md and 站点经验库/<domain>/impact-regression.md when the entry point, endpoint, field, protection state, or eval changes.
List commands/tools used and the required replay/diff/schema regression checks.

Evidence Discipline:

Algorithm restoration, request replay, and runtime environment work require their own evidence and downstream skill handoff when they go beyond entry location.
Fingerprint and risk-control fields must carry source, capture id, replay effect, and freshness status before reuse.
Do not hardcode request headers, fingerprints, cookies, tokens, signatures, timestamps, or session-derived values.

Governance:

Before expanding across market/stage/session, require separate evidence for each scope.
Before claiming concurrency support, require a concurrency ladder and session/cache/fingerprint isolation evidence.
If evidence is missing, stop at unverified and write the missing capture requirement instead of guessing.

定位加密参数 $ARGUMENTS 的生成入口。

目标：找到生成该参数的函数位置（脚本 URL + 行列号 + 函数名 + 调用路径）。

策略选择

根据信号选择策略，不要按固定顺序执行：

优先静态搜索：用 search_in_sources 搜参数名（带 excludeMinified=false）。大多数情况下直接找到赋值位置，然后读上下文追溯来源。

静态搜不到时用 XHR 断点：break_on_xhr 设在请求 URL 特征上，刷新页面触发。断点命中后从调用栈中找业务代码帧，用 evaluate_on_callframe 检查变量。

两种策略可以组合：先静态搜索定位赋值位置，再在赋值处设断点动态验证。

领域知识

agent 在逆向分析中容易踩的坑，这些是无法通过推理得出的经验：

加密参数的 3 种常见架构

业务代码直接赋值 — 在请求函数中 headers["x-sign"] = encrypt(data)。静态搜索直接找到。
请求拦截器统一加签 — axios interceptor 或 fetch wrapper 中统一添加。搜参数名可能只在拦截器中出现一次。
外部安全 SDK — 独立 JS 文件（通常混淆）挂载全局对象（如 window.h5sign），业务代码调用其方法。静态搜索能找到调用处，但 SDK 内部代码全被混淆。

OB 混淆的影响

当加密逻辑在 OB 混淆的文件中（特征：_0x 前缀、大型字符串数组、RC4 解密函数），所有字符串都被加密，静态搜索在该文件内无法匹配任何明文。但调用该文件的业务代码通常未混淆，从业务代码侧搜索更高效。

XHR 断点命中时的堆栈特点

XHR 断点命中在 send() 调用处，调用栈底部通常是框架代码（axios/fetch wrapper）。加密逻辑在栈的中上层。直接跳过底部框架帧，关注业务代码帧。

反模式

不要反复 step_into — 容易掉进框架响应式系统（Vue reactivity、React fiber）。用 evaluate_on_callframe 直接检查变量比单步跟踪高效得多。
不要在 OB 混淆文件中搜字符串 — 所有明文都被加密了，搜不到。从非混淆的调用方搜。
不要频繁刷新页面 — 每次刷新所有 scriptId 失效。设好断点再刷新，一次到位。
断点命中时优先用 evaluate_on_callframe 指定帧 — evaluate_script 在暂停时会自动 fallback 到顶层帧，但如果需要检查特定调用帧的变量，必须用 evaluate_on_callframe 指定 frameIndex。

Tool Policy

开始实现前 Read ~/.claude/skills/karpathy-guidelines/SKILL.md,确认 4 条原则:Think Before Coding / Simplicity First / Surgical Changes / Goal-Driven Execution。这是基础层规范,所有执行类 skill 强制依赖。
遇到逆向运行时问题(断点/时间/cookie/TLS 指纹/风控恢复/接口变更)Read ~/.claude/skills/oh_my_reverse_skill/99-SKILLS治理/10-逆向运行时常见问题.md。
输出结论、扩范围或做并发前 Read ~/.claude/skills/oh_my_reverse_skill/99-SKILLS治理/11-AI事实证据规约.md / 12-反泛化与任务收敛规约.md / 13-并发指纹与会话隔离规约.md。
改端点/字段/状态/保护/实现/eval 前后 Read 14-知识图谱行程与关联规约.md / 15-AI变更风险与回归校验规约.md,并更新 knowledge-graph.md / impact-regression.md。

完成标准

找到以下信息即为完成：

入口位置：
- 参数：$ARGUMENTS
- 脚本：https://example.com/static/js/main.abc123.js
- 位置：第 X 行，第 Y 列
- 函数：functionName (或 anonymous)
- 调用路径：request → addSign → encrypt
- 加密类型：[标准算法名 | 外部SDK | 未知/需解混淆]

只找入口，不做算法还原。

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name	find-crypto-entry
standard_type	internal_tool
description	Internal/support tool for locating the JS source of one concrete encrypted request field, sign, x-sign, authKey, or token. Use directly only when the user explicitly asks for an atomic entry-location task such as "找加密入口", "签名怎么算", or "这个请求头字段哪里生成"; otherwise let reverse-js-crawler or website-314-api-delivery choose it. Do not trigger for generic crawler delivery, ordinary request inspection, challenge/WAF backend acceptance, or non-encrypted parameters.
argument-hint	["参数名"]
platforms	["web","h5"]

find-crypto-entry

Hardened Tool Governance

Version: 0.5.0

Change log: 0.5.0 adds structured eval coverage, graph/impact examples, and a hard delivery gate for evidence-first crypto-entry work.

Workflow:

Use references/governance.md before final output, especially when the target field affects endpoints, request headers, request body, cache state, session state, or evals.
Use references/graph-impact-examples.md when writing node/edge updates or impact-regression records.
Treat the final observed API request/response and captured call stack as the source of truth. Do not infer hidden endpoints, parameters, cookies, tokens, device IDs, signatures, or risk tokens.

Success Criteria:

Output the parameter, script URL, line/column or searchable offset, function name, call path, observed request URL, and evidence pointer.
Classify every important claim as observed, derived, assumed, or unverified.
Update 站点经验库/<domain>/knowledge-graph.md and 站点经验库/<domain>/impact-regression.md when the entry point, endpoint, field, protection state, or eval changes.
List commands/tools used and the required replay/diff/schema regression checks.

Evidence Discipline:

Algorithm restoration, request replay, and runtime environment work require their own evidence and downstream skill handoff when they go beyond entry location.
Fingerprint and risk-control fields must carry source, capture id, replay effect, and freshness status before reuse.
Do not hardcode request headers, fingerprints, cookies, tokens, signatures, timestamps, or session-derived values.

Governance:

Before expanding across market/stage/session, require separate evidence for each scope.
Before claiming concurrency support, require a concurrency ladder and session/cache/fingerprint isolation evidence.
If evidence is missing, stop at unverified and write the missing capture requirement instead of guessing.

定位加密参数 $ARGUMENTS 的生成入口。

目标：找到生成该参数的函数位置（脚本 URL + 行列号 + 函数名 + 调用路径）。

策略选择

根据信号选择策略，不要按固定顺序执行：

优先静态搜索：用 search_in_sources 搜参数名（带 excludeMinified=false）。大多数情况下直接找到赋值位置，然后读上下文追溯来源。

静态搜不到时用 XHR 断点：break_on_xhr 设在请求 URL 特征上，刷新页面触发。断点命中后从调用栈中找业务代码帧，用 evaluate_on_callframe 检查变量。

两种策略可以组合：先静态搜索定位赋值位置，再在赋值处设断点动态验证。

领域知识

agent 在逆向分析中容易踩的坑，这些是无法通过推理得出的经验：

加密参数的 3 种常见架构

业务代码直接赋值 — 在请求函数中 headers["x-sign"] = encrypt(data)。静态搜索直接找到。
请求拦截器统一加签 — axios interceptor 或 fetch wrapper 中统一添加。搜参数名可能只在拦截器中出现一次。
外部安全 SDK — 独立 JS 文件（通常混淆）挂载全局对象（如 window.h5sign），业务代码调用其方法。静态搜索能找到调用处，但 SDK 内部代码全被混淆。

OB 混淆的影响

XHR 断点命中时的堆栈特点

XHR 断点命中在 send() 调用处，调用栈底部通常是框架代码（axios/fetch wrapper）。加密逻辑在栈的中上层。直接跳过底部框架帧，关注业务代码帧。

反模式

不要反复 step_into — 容易掉进框架响应式系统（Vue reactivity、React fiber）。用 evaluate_on_callframe 直接检查变量比单步跟踪高效得多。
不要在 OB 混淆文件中搜字符串 — 所有明文都被加密了，搜不到。从非混淆的调用方搜。
不要频繁刷新页面 — 每次刷新所有 scriptId 失效。设好断点再刷新，一次到位。
断点命中时优先用 evaluate_on_callframe 指定帧 — evaluate_script 在暂停时会自动 fallback 到顶层帧，但如果需要检查特定调用帧的变量，必须用 evaluate_on_callframe 指定 frameIndex。

Tool Policy

开始实现前 Read ~/.claude/skills/karpathy-guidelines/SKILL.md,确认 4 条原则:Think Before Coding / Simplicity First / Surgical Changes / Goal-Driven Execution。这是基础层规范,所有执行类 skill 强制依赖。
遇到逆向运行时问题(断点/时间/cookie/TLS 指纹/风控恢复/接口变更)Read ~/.claude/skills/oh_my_reverse_skill/99-SKILLS治理/10-逆向运行时常见问题.md。
输出结论、扩范围或做并发前 Read ~/.claude/skills/oh_my_reverse_skill/99-SKILLS治理/11-AI事实证据规约.md / 12-反泛化与任务收敛规约.md / 13-并发指纹与会话隔离规约.md。
改端点/字段/状态/保护/实现/eval 前后 Read 14-知识图谱行程与关联规约.md / 15-AI变更风险与回归校验规约.md,并更新 knowledge-graph.md / impact-regression.md。

完成标准

找到以下信息即为完成：

入口位置：
- 参数：$ARGUMENTS
- 脚本：https://example.com/static/js/main.abc123.js
- 位置：第 X 行，第 Y 列
- 函数：functionName (或 anonymous)
- 调用路径：request → addSign → encrypt
- 加密类型：[标准算法名 | 外部SDK | 未知/需解混淆]

只找入口，不做算法还原。