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Re Ai Triage

ASecurity

AI 模型分析第一入口(分流器):识别输入形态——模型文件走文件层逆向(re-ai-model)、 仅有 API 走行为层评估(re-ai-attack)、恶意行为走恶意分析。 触发词:AI模型分析、AI模型安全、模型文件、模型泄露、模型逆向、模型分析入口。

54 stars
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Added 9/19/2026
datapythongoapi

Works with

api

Security Analysis

A100/100

Scanned 9/19/2026

Install to Claude Code

$npx -y skills add dslsdzc/rev-skills --skill re-ai-triage --agent claude-code

Installs into .claude/skills of the current project.

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Files
SKILL.md
---
name: re-ai-triage
type: atomic
description: >
  AI 模型分析第一入口(分流器):识别输入形态——模型文件走文件层逆向(re-ai-model)、
  仅有 API 走行为层评估(re-ai-attack)、恶意行为走恶意分析。
  触发词:AI模型分析、AI模型安全、模型文件、模型泄露、模型逆向、模型分析入口。
capabilities: [triage]
---

# AI 模型分析入口(分流器)

## 任务分类器(输入形态 → 路径)

拿到 AI 相关目标后先判输入形态,命中即转对应技能:

| 输入形态 | 路径 |
|---|---|
| 拿到模型文件(.onnx / .pt / .pth / .safetensors / .tflite) | → **[[re-ai-model]]**(文件层:格式解析 / 结构还原 / 权重提取 / 文件级水印) |
| 只有 API(无文件,黑盒接口) | → **[[re-ai-attack]]**(行为层:extraction / fingerprint / privacy / robustness 评估;guard 授权前置) |
| 文件 + API 都有 | → 先 [[re-ai-model]](文件侧取证)→ 再 [[re-ai-attack]](行为侧验证) |
| 发现恶意行为(投毒 / 后门 / 恶意载荷 / 下载执行) | → 恶意分析(当前:[[re-ai-model]] 安全边界处理 + [[re-behavior]];未来独立 re-ai-malware 承接) |
| 模型被打包进可执行(PyInstaller/pyarmor 等) | → 先 [[re-binary-core]] 拆包 → 拆出的模型文件回本技能分流 |

## 何时使用 / 何时不用

- 用:用户说「分析这个模型 / AI 模型安全 / 模型泄露」但未指明输入形态——先分流
- 用:不确定目标是文件层还是行为层时——先识别再转
- 不用:输入形态已明确(直接进 [[re-ai-model]] 或 [[re-ai-attack]],不绕本技能)
- 不用:非 AI 目标(走全局入口 [[re-analyze]])
- 不用:训练 / 微调 / 部署(非逆向)

## 工具准备

本技能只做识别与分流,工具轻量:

### python3 / file —— 模型文件识别

- python3 安装与验证见 [[re-python]] 工具准备
- `file`:Linux `apt install file` / `dnf install file` / `pacman -S file`(多数预装);验证 `file --version`
- 验证:`python3 -c "import struct"`(标准库)

### 模型库探测(判断目标依赖,不加载模型)

- `pip list 2>/dev/null | grep -iE 'torch|tensorflow|onnx'`——确认本机可解析目标格式;缺失时由下游技能引导安装

## 操作步骤

1. **输入形态识别**:
   - 用户给了路径/文件 → 先 `file <path>`(onnx:`file` 常报 `data`——以 `xxd` 首字节 protobuf 头(`08 08`)+ `strings` producer 名辅助识别;safetensors:`JSON metadata` 头;pt/pth:`pickle` 或 zip 容器;tflite:`tflite` 标识)→ 转 [[re-ai-model]]
   - 用户只有 API 端点/查询能力 → 转 [[re-ai-attack]]
   - 两者都有 → 按任务分类器先文件后行为
2. **目标归属确认**:文件/API 的持有方与授权(自有 / 授权测试 / CTF·研究)——行为层评估前必须确认([[re-ai-attack]] guard 前置;授权上下文见 triage 第 0 步 `RE_AUTH`)
3. **转交与记录**:明确转交技能 + 会话变量(`RE_GOAL`、`RE_AUTH`、输入形态标记),不在本技能做深度分析

## 跨域联合

- [[re-managed]]:本技能是其 AI 分支的第一跳(re-managed → re-ai-triage → re-ai-model / re-ai-attack)
- [[re-ai-model]]:文件层下游
- [[re-ai-attack]]:行为层下游(guard 授权前置)
- [[re-binary-core]]:模型打包进可执行时的拆包前置
- [[re-behavior]]:恶意行为侧协作(投毒/后门的行为判定)

## 常见坑与陷阱

- **拿文件名猜格式**:`.pt` 可能是 pickle 也可能是 zip 容器(torch 新格式)、`.bin` 可能是任意权重 dump——以 `file` 输出与魔数为准,不靠扩展名
- **分流过深**:本技能只识别与转交,不展开分析——在分流阶段做深度分析会与下游重复
- **授权前置遗漏**:行为层评估([[re-ai-attack]])有 guard 授权要求——转交前先确认 `RE_AUTH`,未知归属时先询问,不直接进入行为层

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