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Agent Skill · 研究检索

binary-triage(二元分类)

binary-triage 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

binary-triage 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 34,485。

总安装 2,221周安装 89GitHub Stars 713下载 719核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:binary-triage(二元分类)
来源仓库:https://github.com/cyberkaida/reverse-engineering-assistant
仓库路径:skills/binary-triage
安装命令:
npx skills add https://github.com/cyberkaida/reverse-engineering-assistant --skill binary-triage
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/cyberkaida/reverse-engineering-assistant --skill binary-triage

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

系统化扫描二进制文件内存布局与导入表,标记可疑函数与异常行为。适合初步筛查恶意软件或未知程序,生成下一步分析任务清单。依赖 ReVa MCP 工具链,输出为结构化 JSON 便于自动化处理。不承诺深度解密,重点在于快速暴露潜在兴趣点供人工研判。

binary-triage 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/binary-triage

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/cyberkaida/reverse-engineering-assistant --ski…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

binary-triage 怎么安装?

在终端执行 npx skills add https://github.com/cyberkaida/reverse-engineering-assistant --skill binary-…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

binary-triage 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

binary-triage 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

binary-triage 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

binary-triage 用的人多吗?

公开数据是累计安装 2,221 次,近一周安装 89 次,下载 719 次,GitHub 713 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

binary-triage 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
binary-triage

二元分类 · 本页

2,221713调用外部服务未明确未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Binary Triage

Instructions

We are triaging a binary to quickly understand what it does. This is an initial survey, not deep analysis. Our goal is to:

  1. Identify key components and behaviors
  2. Flag suspicious or interesting areas
  3. Create a task list of next steps for deeper investigation

Binary triage with ReVa

Follow this systematic workflow using ReVa's MCP tools:

1. Identify the Program

  • Use get-current-program to see the active program
  • Or use list-project-files to see available programs in the project
  • Note the programPath (e.g., "/Hatchery.exe") for use in subsequent tools

2. Survey Memory Layout

  • Use get-memory-blocks to understand the binary structure
  • Examine key sections:

- .text - executable code - .data - initialized data - .rodata - read-only data (strings, constants) - .bss - uninitialized data

  • Flag unusual characteristics:

- Unusually large sections - Packed/encrypted sections - Executable data sections - Writable code sections

3. Survey Strings

  • Use get-strings-count to see total string count
  • Use get-strings with pagination (100-200 strings at a time)
  • Look for indicators of functionality or malicious behavior:

- Network: URLs, IP addresses, domain names, API endpoints - File System: File paths, registry keys, configuration files - APIs: Function names, library references - Messages: Error messages, debug strings, log messages - Suspicious Keywords: admin, password, credential, token, crypto, encrypt, decrypt, download, execute, inject, shellcode, payload

4. Survey Symbols and Imports

  • Use get-symbols-count with includeExternal=true to count imports
  • Use get-symbols with includeExternal=true and filterDefaultNames=true
  • Focus on external symbols (imports from libraries)
  • Flag interesting/suspicious imports by category:

- Network APIs: connect, send, recv, WSAStartup, getaddrinfo, curl_*, socket - File I/O: CreateFile, WriteFile, ReadFile, fopen, fwrite, fread - Process Manipulation: CreateProcess, exec, fork, system, WinExec, ShellExecute - Memory Operations: VirtualAlloc, VirtualProtect, mmap, mprotect - Crypto: CryptEncrypt, CryptDecrypt, EVP_*, AES_*, bcrypt, RC4 - Anti-Analysis: IsDebuggerPresent, CheckRemoteDebuggerPresent, ptrace - Registry: RegOpenKey, RegSetValue, RegQueryValue

  • Note the ratio of imports to total symbols (heavy import usage may indicate reliance on libraries)

5. Survey Functions

  • Use get-function-count with filterDefaultNames=true to count named functions
  • Use get-function-count with filterDefaultNames=false to count all functions
  • Calculate ratio of named vs unnamed functions (high unnamed ratio = stripped binary)
  • Use get-functions with filterDefaultNames=true to list named functions
  • Identify key functions:

- Entry points: entry, start, _start - Main functions: main, WinMain, DllMain, _main - Suspicious names: If not stripped, look for revealing function names

6. Cross-Reference Analysis for Key Findings

  • For interesting strings found in Step 3:

- Use find-cross-references with direction="to" and includeContext=true - Identify which functions reference suspicious strings

  • For suspicious imports found in Step 4:

- Use find-cross-references with direction="to" and includeContext=true - Identify which functions call suspicious APIs

  • This helps prioritize which functions need detailed examination

7. Selective Initial Decompilation

  • Use get-decompilation on entry point or main function

- Set limit=30 to get ~30 lines initially - Set includeIncomingReferences=true to see callers - Set includeReferenceContext=true for context snippets

  • Use get-decompilation on 1-2 suspicious functions identified in Step 6

- Set limit=20-30 for quick overview

  • Look for high-level patterns:

- Loops (encryption/decryption routines) - Network operations - File operations - Process creation - Suspicious control flow (obfuscation indicators)

  • Do not do deep analysis yet - this is just to understand general behavior

8. Document Findings and Create Task List

  • Use the TodoWrite tool to create an actionable task list with items like:

- "Investigate string 'http://malicious-c2.com' (referenced at 0x00401234)" - "Decompile function sub_401000 (calls VirtualAlloc + memcpy + CreateThread)" - "Analyze crypto usage in function encrypt_payload (uses CryptEncrypt)" - "Trace anti-debugging checks (IsDebuggerPresent at 0x00402000)" - "Examine packed section.UPX0 for unpacking routine"

  • Each todo should be:

- Specific (include addresses, function names, strings) - Actionable (what needs to be investigated) - Prioritized (most suspicious first)

Output Format

Present triage findings to the user in this structured format:

Program Overview

  • Name: [Program name from programPath]
  • Type: [Executable type - PE, ELF, Mach-O, etc.]
  • Platform: [Windows, Linux, macOS, etc.]

Memory Layout

  • Total Size: [Size in bytes/KB/MB]
  • Key Sections: [List main sections with sizes and permissions]
  • Unusual Characteristics: [Any packed/encrypted/suspicious sections]

String Analysis

  • Total Strings: [Count from get-strings-count]
  • Notable Findings: [Bullet list of interesting strings with context]
  • Suspicious Indicators: [URLs, IPs, suspicious keywords found]

Import Analysis

  • Total Symbols: [Count from get-symbols-count]
  • External Imports: [Count of external symbols]
  • Key Libraries: [Main libraries imported]
  • Suspicious APIs: [Categorized list of concerning imports]

Function Analysis

  • Total Functions: [Count with filterDefaultNames=false]
  • Named Functions: [Count with filterDefaultNames=true]
  • Stripped Status: [Yes/No based on ratio]
  • Entry Point: [Address and name]
  • Main Function: [Address and name]
  • Key Functions: [List of important functions identified]

Suspicious Indicators

[Bulleted list of red flags discovered, prioritized by severity]

Recommended Next Steps

[Present the task list created in Step 8]

  • Each item should be specific and actionable
  • Prioritize by severity/importance
  • Include addresses, function names, and context

Important Notes

  • Speed over depth: This is triage, not full analysis. Move quickly through steps.
  • Use pagination: Don't request thousands of strings/functions at once. Use chunks of 100-200.
  • Focus on anomalies: Flag things that are unusual, suspicious, or interesting.
  • Context is key: When using cross-references, enable includeContext=true for code snippets.
  • Create actionable todos: Each next step should be specific enough for another agent to execute.
  • Be systematic: Follow all 8 steps in order for comprehensive coverage.

平台分布

Codex

39.92%
按下载量换算287

Claude

28.75%
按下载量换算207

Cursor

18.71%
按下载量换算135

Gemini CLI

10.1%
按下载量换算73

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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