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Agent Skill · 研究检索

password-recovery(密码恢复)

password-recovery 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。

password-recovery 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,权限为权限未标注;许可证为 MIT,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 41,140。

总安装 1,213周安装 34GitHub Stars 93下载 280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
MIT

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:password-recovery(密码恢复)
来源仓库:https://github.com/letta-ai/skills
仓库路径:skills/password-recovery
安装命令:
npx skills add https://github.com/letta-ai/skills --skill password-recovery
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/letta-ai/skills --skill password-recovery

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。

用于查找、检索和筛选相关信息。password-recovery 属于研究检索类 Skill,可作为该场景下的辅助能力补充。适合根据关键词或任务场景快速定位候选结果。可结合来源仓库和原始 README 核验具体用法。安装前建议确认权限范围和维护状态。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。注意是否会触发联网或文件读写操作。

来源仓库内路径:skills/password-recovery

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/letta-ai/skills --skill password-recovery;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

    权限没有明确标注,第一次使用时只给一个无关紧要的任务,观察它到底读了哪些文件和网络。

常见问题

6 条

password-recovery 怎么安装?

在终端执行 npx skills add https://github.com/letta-ai/skills --skill password-recovery。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

password-recovery 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。

password-recovery 需要什么权限?

权限级别没有明确标注。第一次使用时建议只给无关紧要的任务,观察它实际读写了哪些内容。

password-recovery 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

password-recovery 用的人多吗?

公开数据是累计安装 1,213 次,近一周安装 34 次,下载 280 次,GitHub 93 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。

password-recovery 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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 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
password-recovery

密码恢复 · 本页

1,21393权限未标注MIT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

Password Recovery

Overview

This skill provides guidance for digital forensic recovery tasks involving the extraction of passwords or sensitive data from disk images, deleted files, and binary data. It covers systematic approaches to environment assessment, file identification, pattern searching, fragment reconstruction, and result validation.

Environment Assessment (Critical First Step)

Before attempting any recovery operations, assess the working environment:

  1. Identify available tools: Run which strings hexdump xxd file binwalk to determine available forensic utilities
  2. Understand access boundaries: In containerized environments, host filesystems and block devices are typically inaccessible
  3. Map the working directory: Execute find /app -type f 2>/dev/null or equivalent to discover all available files
  4. Avoid premature exploration: Do not attempt to access /proc/kcore, raw block devices, or Docker overlay directories before confirming access permissions

File Discovery and Identification

Systematic File Location

To locate potential data sources:

  1. List all files recursively in the working directory first
  2. Identify binary files: Use file * on discovered files to determine types
  3. Look for obvious locations: Directory names like disks/, images/, backup/ often contain relevant data
  4. Check common extensions: .dat, .img, .bin, .raw, .dd files are primary candidates

File Type Analysis

Always run file type identification on unknown binary files:

file <filename>

Common indicators:

  • "data" - Generic binary, requires further analysis
  • "Zip archive" - May contain recoverable data, attempt extraction
  • "disk image" - Direct forensic target
  • Presence of "PK" bytes (hex: 50 4B) suggests ZIP archive structure

Pattern Searching Strategies

Initial Broad Search

Start with inclusive patterns to identify potential matches:

strings <file> | grep -E '[A-Z0-9]{8,}'

Refined Pattern Search

When password format is known, construct specific regex patterns:

# For alphanumeric passwords of specific length
strings <file> | grep -E '^[A-Z0-9]{23}$'

# For partial fragments
strings <file> | grep -E '[A-Z0-9]{10,15}'

Binary-Level Search

For data not extractable via strings:

# If xxd is available
xxd <file> | grep -i '<pattern>'

# Python fallback for hex analysis
python3 -c "
import sys
with open('<file>', 'rb') as f:
    data = f.read()
    # Search for patterns in raw bytes
    for i in range(len(data) - 10):
        chunk = data[i:i+20]
        if chunk.isalnum() or b'<pattern>' in chunk:
            print(f'Offset {i}: {chunk}')
"

Fragment Reconstruction

Identifying Fragments

Fragments may occur due to:

  • File system allocation boundaries
  • Compression artifacts
  • Partial file deletion
  • Archive structure overhead

Fragment Combination Strategy

When multiple potential fragments are found:

  1. Document all candidates with their byte offsets
  2. Check length requirements: If target length is known, verify fragment combinations sum correctly
  3. Test all orderings: Fragments may appear out of order in storage
  4. Validate each combination against known criteria before concluding

Combination Validation Checklist

Before accepting a combined result:

  • Total length matches expected value
  • Character set matches requirements (alphanumeric, special chars, etc.)
  • No duplicate characters if uniqueness required
  • Passes any provided validation criteria

Verification Strategies

Multi-Criteria Validation

When multiple conditions must be met, verify each explicitly:

password = "CANDIDATE_PASSWORD"
checks = {
    "length": len(password) == 23,
    "alphanumeric": password.isalnum(),
    "uppercase_letters": password.isupper(),
    # Add task-specific criteria
}
print(f"All checks passed: {all(checks.values())}")
for check, result in checks.items():
    print(f"  {check}: {result}")

Exhaustive Search Confirmation

After finding a candidate, verify no other matches exist:

# Confirm uniqueness of the pattern in the source
grep -c '<pattern>' <file>

Common Pitfalls to Avoid

Environment-Related Mistakes

  1. Assuming host access: Container environments restrict access to host filesystems
  2. Using unavailable tools: Verify tool availability before attempting complex commands
  3. Broad filesystem searches: Start with the working directory, not root-level exploration

Analysis Mistakes

  1. Ignoring file type identification: Always run file on unknown binaries
  2. Missing archive structures: Check for ZIP/archive signatures (PK headers) in binary data
  3. Single-pass searching: Use multiple search strategies; strings may miss embedded data

Reconstruction Mistakes

  1. Assuming fragment order: Storage order may not match original data order
  2. Incomplete validation: Verify all criteria, not just length or format
  3. Premature conclusion: Search for alternative fragment combinations before finalizing

Workflow Summary

  1. Environment Assessment: Identify tools, boundaries, and available data
  2. File Discovery: Map all files, identify types, prioritize candidates
  3. Initial Analysis: Run file, strings, and broad pattern searches
  4. Deep Analysis: Binary-level examination if initial search insufficient
  5. Fragment Collection: Document all potential fragments with offsets
  6. Reconstruction: Combine fragments, test orderings
  7. Validation: Verify against all known criteria
  8. Confirmation: Ensure no alternative matches exist

平台分布

Claude Code

27.66%
按下载量换算77

Gemini CLI

26.11%
按下载量换算73

Codex

17.29%
按下载量换算48

Antigravity

14.69%
按下载量换算41

OpenCode

8.85%
按下载量换算25

windsurf

4.05%
按下载量换算11

安全审计

Gen Agent Trust Hub

可疑

Socket

可疑

Snyk

未通过

权限和风险

权限未标注

当前来源未能明确判断权限范围,默认进入异常复核队列。

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。

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