Token导航 LogoToken导航

Agent Skill · 研究检索

analyzing-windows-lnk-files-for-artifacts(分析 Windows lnk 文件中的工件)

analyzing-windows-lnk-files-for-artifacts 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。

analyzing-windows-lnk-files-for-artifacts 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,权限为执行命令;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 69,747。

总安装 217周安装 25GitHub Stars 5,910下载 53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:analyzing-windows-lnk-files-for-artifacts(分析 Windows lnk 文件中的工件)
来源仓库:https://github.com/mukul975/anthropic-cybersecurity-skills
仓库路径:skills/analyzing-windows-lnk-files-for-artifacts
安装命令:
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzing-windows-lnk-files-for-artifacts
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/mukul975/anthropic-cybersecurity-skills --skill analyzing-windows-lnk-files-for-artifacts

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。

分析 Windows LNK 快捷方式文件,重建用户文件访问历史。可追踪网络共享、USB 设备访问路径与文档打开证据。适用于 forensic timeline 构建与远程系统访问验证。安装来自 GitHub,需 LNK 文件或解析工具支持。

analyzing-windows-lnk-files-for-artifacts 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/analyzing-windows-lnk-files-for-artifacts

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/mukul975/anthropic-cybersecurity-skills --skil…;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

    它需要执行命令,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

analyzing-windows-lnk-files-for-artifacts 怎么安装?

在终端执行 npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzin…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

analyzing-windows-lnk-files-for-artifacts 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。

analyzing-windows-lnk-files-for-artifacts 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzing-windows-lnk-files-for-artifacts 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

analyzing-windows-lnk-files-for-artifacts 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。

analyzing-windows-lnk-files-for-artifacts 用的人多吗?

公开数据是累计安装 217 次,近一周安装 25 次,下载 53 次,GitHub 5,910 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。

analyzing-windows-lnk-files-for-artifacts 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 5,910 星,维护活跃度相对可查。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 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

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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
analyzing-windows-lnk-files-for-artifacts

分析 Windows lnk 文件中的工件 · 本页

2175,910执行命令未明确通过

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

Analyzing Windows LNK Files for Artifacts

When to Use

  • When reconstructing user file access history from Windows shortcut files
  • For tracking accessed files, network shares, and removable media
  • During investigations to prove a user opened specific documents
  • When correlating file access with other timeline artifacts
  • For identifying accessed paths on remote systems or USB devices

Prerequisites

  • Access to LNK files from forensic image (Recent, Desktop, Quick Launch)
  • LECmd (Eric Zimmerman), python-lnk, or LnkParser for analysis
  • Understanding of LNK file structure (Shell Link Binary format)
  • Knowledge of LNK file locations on Windows systems
  • Forensic workstation with analysis tools installed

Workflow

Step 1: Collect LNK Files from Forensic Image

# Mount forensic image
mount -o ro,loop,offset=$((2048*512)) /cases/case-2024-001/images/evidence.dd /mnt/evidence

mkdir -p /cases/case-2024-001/lnk/{recent,desktop,startup,custom}

# Copy Recent items LNK files (primary source)
cp /mnt/evidence/Users/*/AppData/Roaming/Microsoft/Windows/Recent/*.lnk \
   /cases/case-2024-001/lnk/recent/ 2>/dev/null

# Copy automatic destinations (Jump Lists)
cp /mnt/evidence/Users/*/AppData/Roaming/Microsoft/Windows/Recent/AutomaticDestinations/*.automaticDestinations-ms \
   /cases/case-2024-001/lnk/recent/ 2>/dev/null

# Copy custom destinations (pinned Jump List items)
cp /mnt/evidence/Users/*/AppData/Roaming/Microsoft/Windows/Recent/CustomDestinations/*.customDestinations-ms \
   /cases/case-2024-001/lnk/custom/ 2>/dev/null

# Copy Desktop shortcuts
cp /mnt/evidence/Users/*/Desktop/*.lnk /cases/case-2024-001/lnk/desktop/ 2>/dev/null

# Copy Startup folder shortcuts (persistence)
cp /mnt/evidence/Users/*/AppData/Roaming/Microsoft/Windows/Start\ Menu/Programs/Startup/*.lnk \
   /cases/case-2024-001/lnk/startup/ 2>/dev/null
cp "/mnt/evidence/ProgramData/Microsoft/Windows/Start Menu/Programs/Startup"/*.lnk \
   /cases/case-2024-001/lnk/startup/ 2>/dev/null

# Find all LNK files on the system
find /mnt/evidence/ -name "*.lnk" -type f 2>/dev/null > /cases/case-2024-001/lnk/all_lnk_locations.txt

# Count and hash
ls /cases/case-2024-001/lnk/recent/ | wc -l
sha256sum /cases/case-2024-001/lnk/recent/*.lnk > /cases/case-2024-001/lnk/lnk_hashes.txt 2>/dev/null

Step 2: Parse LNK Files with LECmd

# Using Eric Zimmerman's LECmd (Windows or via Mono)
# Process all LNK files in a directory
LECmd.exe -d "C:\cases\lnk\recent\" --csv "C:\cases\analysis\" --csvf lnk_analysis.csv

# Process a single LNK file with verbose output
LECmd.exe -f "C:\cases\lnk\recent\document.pdf.lnk"

# Process Jump List files
JLECmd.exe -d "C:\cases\lnk\recent\" --csv "C:\cases\analysis\" --csvf jumplist_analysis.csv

# Output includes:
# - Source file path
# - Target path (file that was accessed)
# - Target creation, modification, access timestamps
# - LNK creation and modification timestamps
# - Working directory
# - Command line arguments
# - Volume serial number and label
# - Drive type (Fixed, Removable, Network)
# - Machine ID (NetBIOS name)
# - MAC address (from tracker database)
# - File size of target

Step 3: Parse LNK Files with Python

pip install LnkParse3

python3 << 'PYEOF'
import LnkParse3
import os, json, csv
from datetime import datetime

lnk_dir = '/cases/case-2024-001/lnk/recent/'
results = []

for filename in sorted(os.listdir(lnk_dir)):
    if not filename.lower().endswith('.lnk'):
        continue

    filepath = os.path.join(lnk_dir, filename)
    try:
        with open(filepath, 'rb') as f:
            lnk = LnkParse3.lnk_file(f)
            info = lnk.get_json()

            parsed = {
                'lnk_file': filename,
                'target_path': '',
                'working_dir': '',
                'arguments': '',
                'target_created': '',
                'target_modified': '',
                'target_accessed': '',
                'file_size': '',
                'drive_type': '',
                'volume_serial': '',
                'volume_label': '',
                'machine_id': '',
                'mac_address': '',
            }

            # Extract header timestamps
            header = info.get('header', {})
            parsed['target_created'] = str(header.get('creation_time', ''))
            parsed['target_modified'] = str(header.get('modified_time', ''))
            parsed['target_accessed'] = str(header.get('accessed_time', ''))
            parsed['file_size'] = str(header.get('file_size', ''))

            # Extract link info
            link_info = info.get('link_info', {})
            if link_info:
                local_path = link_info.get('local_base_path', '')
                network_path = link_info.get('common_network_relative_link', {}).get('net_name', '')
                parsed['target_path'] = local_path or network_path

                vol_info = link_info.get('volume_id', {})
                if vol_info:
                    parsed['drive_type'] = str(vol_info.get('drive_type', ''))
                    parsed['volume_serial'] = str(vol_info.get('drive_serial_number', ''))
                    parsed['volume_label'] = str(vol_info.get('volume_label', ''))

            # Extract string data
            string_data = info.get('string_data', {})
            parsed['working_dir'] = str(string_data.get('working_dir', ''))
            parsed['arguments'] = str(string_data.get('command_line_arguments', ''))

            # Extract tracker data (machine ID and MAC)
            extra = info.get('extra', {})
            tracker = extra.get('DISTRIBUTED_LINK_TRACKER_BLOCK', {})
            if tracker:
                parsed['machine_id'] = str(tracker.get('machine_id', ''))
                parsed['mac_address'] = str(tracker.get('mac_address', ''))

            results.append(parsed)

            # Print summary
            print(f"\n{filename}")
            print(f"  Target: {parsed['target_path']}")
            print(f"  Modified: {parsed['target_modified']}")
            print(f"  Drive: {parsed['drive_type']} (Serial: {parsed['volume_serial']})")
            if parsed['machine_id']:
                print(f"  Machine: {parsed['machine_id']}")

    except Exception as e:
        print(f"  Error parsing {filename}: {e}")

# Write results to CSV
with open('/cases/case-2024-001/analysis/lnk_analysis.csv', 'w', newline='') as f:
    writer = csv.DictWriter(f, fieldnames=results[0].keys() if results else [])
    writer.writeheader()
    writer.writerows(results)

print(f"\n\nTotal LNK files parsed: {len(results)}")
PYEOF

Step 4: Analyze for Investigative Value

# Identify files accessed from removable media
python3 << 'PYEOF'
import csv

with open('/cases/case-2024-001/analysis/lnk_analysis.csv') as f:
    reader = csv.DictReader(f)

    print("=== FILES ACCESSED FROM REMOVABLE MEDIA ===\n")
    removable = []
    network = []

    for row in reader:
        if 'DRIVE_REMOVABLE' in row.get('drive_type', '').upper() or \
           'removable' in row.get('drive_type', '').lower():
            removable.append(row)
            print(f"  {row['target_modified']} | {row['target_path']} | Vol: {row['volume_serial']}")

        if 'network' in row.get('drive_type', '').lower() or \
           row.get('target_path', '').startswith('\\\\'):
            network.append(row)

    print(f"\n=== FILES ACCESSED FROM NETWORK SHARES ===\n")
    for row in network:
        print(f"  {row['target_modified']} | {row['target_path']}")

    print(f"\nRemovable media files: {len(removable)}")
    print(f"Network share files: {len(network)}")

    # Check for unique machines (tracker data)
    machines = set()
    for row in [*removable, *network]:
        if row.get('machine_id'):
            machines.add(row['machine_id'])
    if machines:
        print(f"\nMachine IDs found: {machines}")
PYEOF

# Check Startup folder LNK files for persistence
echo "=== STARTUP FOLDER SHORTCUTS (PERSISTENCE) ===" > /cases/case-2024-001/analysis/startup_persistence.txt
for lnk in /cases/case-2024-001/lnk/startup/*.lnk; do
    python3 -c "
import LnkParse3
with open('$lnk', 'rb') as f:
    lnk = LnkParse3.lnk_file(f)
    info = lnk.get_json()
    target = info.get('link_info', {}).get('local_base_path', 'Unknown')
    args = info.get('string_data', {}).get('command_line_arguments', '')
    print(f'  $(basename $lnk): {target} {args}')
" >> /cases/case-2024-001/analysis/startup_persistence.txt 2>/dev/null
done

Key Concepts

ConceptDescription
Shell Link (.lnk)Windows shortcut file format containing target path, timestamps, and metadata
Target timestampsCreation, modification, and access times of the file the shortcut points to
Volume serial numberUnique identifier of the drive volume where the target file resides
Machine IDNetBIOS name embedded by the Distributed Link Tracking service
MAC addressNetwork adapter MAC from the machine that created the LNK file
Jump ListsRecent and pinned file lists per application (contain embedded LNK data)
Automatic DestinationsSystem-managed Jump List entries for recently opened files
Custom DestinationsUser-pinned Jump List items that persist until manually removed

Tools & Systems

ToolPurpose
LECmdEric Zimmerman command-line LNK file parser with CSV/JSON output
JLECmdEric Zimmerman Jump List parser
LnkParse3Python library for programmatic LNK file analysis
lnk_parserAlternative Python LNK parsing tool
AutopsyForensic platform with LNK file analysis module
KAPEAutomated LNK and Jump List artifact collection
PlasoTimeline tool with LNK file parser for super-timeline creation
LNK ExplorerGUI tool for interactive LNK file examination

Common Scenarios

Scenario 1: Data Exfiltration via USB Drive Analyze Recent folder LNK files for targets on removable drives, correlate volume serial numbers with USBSTOR registry entries, build a list of files accessed from USB devices, establish which documents were opened from the removable drive, correlate with file copy timestamps.

Scenario 2: Malware Persistence via Startup Shortcuts Examine Startup folder LNK files for malicious targets, check target path and arguments for encoded commands or suspicious executables, verify target file exists and examine it, correlate creation timestamp with initial compromise time.

Scenario 3: Network Share Access Investigation Filter LNK files with network paths (UNC targets), identify which network shares were accessed and when, correlate machine IDs with known corporate systems, check if sensitive file servers were accessed outside of normal duties, build access timeline for compliance investigation.

Scenario 4: Document Access Timeline for Legal Proceedings Extract all Recent folder LNK files, build chronological list of documents accessed by the user, identify specific files relevant to the case, present target timestamps showing when files were opened, correlate with email and communication timelines.

Output Format

LNK File Analysis Summary:
  User Profile: suspect_user
  Total LNK Files: 234 (Recent: 198, Desktop: 23, Startup: 5, Other: 8)

  File Access Statistics:
    Local drive (C:):    156 files
    Removable media:     23 files (3 unique volume serials)
    Network shares:      15 files (\\server01, \\fileserver)
    Other drives:        4 files

  Machine IDs Found: DESKTOP-ABC123, LAPTOP-XYZ789
  MAC Addresses: AA:BB:CC:DD:EE:FF, 11:22:33:44:55:66

  Removable Media Access:
    Volume Serial 1234-ABCD:
      2024-01-15 14:32 - E:\Confidential\financial_report.xlsx
      2024-01-15 14:45 - E:\Confidential\customer_database.csv
      2024-01-15 15:00 - E:\Projects\source_code.zip

  Startup Persistence:
    updater.lnk -> C:\ProgramData\svc\updater.exe (SUSPICIOUS)
    OneDrive.lnk -> C:\Users\...\OneDrive.exe (Legitimate)

  Timeline: /cases/case-2024-001/analysis/lnk_analysis.csv

平台分布

Codex

36.2%
按下载量换算19

Claude

28.47%
按下载量换算15

Cursor

18.75%
按下载量换算10

Gemini CLI

9.19%
按下载量换算5

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzing-windows-lnk-files-for-artifacts 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills