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password-recovery密码恢复

Agent Skill

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。

总安装

1,213

周安装

34

GitHub Stars

93

下载量

280
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

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

简介

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。

SKILL.md

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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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

权限需确认

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 warning/failed 结果,不能写成本站确认安全。

来源信息

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