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performing-memory-forensics-with-volatility3执行具有波动性的内存取证 3

Agent Skill

performing-memory-forensics-with-volatility3 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。

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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

2

许可证

unknown

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:performing-memory-forensics-with-volatility3(执行具有波动性的内存取证 3)
来源仓库:https://github.com/mukul975/anthropic-cybersecurity-skills
仓库路径:skills/performing-memory-forensics-with-volatility3
安装命令:
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill performing-memory-forensics-with-volatility3
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 performing-memory-forensics-with-volatility3

简介

使用 volatility3 执行内存取证分析,提取运行时证据。

  • 适用于应急响应、恶意进程检测与内存转储研究。
  • 解析内存结构,查找隐藏进程、网络连接与注入代码。
  • 需具备专业技能,正确解读内存快照内容。
  • performing-memory-forensics-with-volatility3 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Performing Memory Forensics with Volatility 3

When to Use

  • When analyzing a RAM dump from a compromised or suspect system
  • During incident response to identify running malware, injected code, or rootkits
  • When you need to extract credentials, encryption keys, or network connections from memory
  • For detecting process hollowing, DLL injection, or hidden processes
  • When disk-based forensics alone is insufficient and volatile data is critical

Prerequisites

  • Python 3.7+ installed
  • Volatility 3 framework installed (pip install volatility3)
  • Memory dump in raw, ELF, or crash dump format
  • Appropriate symbol tables (ISF files) for the target OS version
  • Sufficient disk space for analysis output (2-3x memory dump size)
  • Optional: YARA rules for malware scanning in memory

Workflow

Step 1: Acquire Memory Dump and Install Volatility 3

# Install Volatility 3
pip install volatility3

# Or install from source for latest features
git clone https://github.com/volatilityfoundation/volatility3.git
cd volatility3
pip install -e .

# Download Windows symbol tables (ISF packs)
# Place in volatility3/symbols/ directory
wget https://downloads.volatilityfoundation.org/volatility3/symbols/windows.zip
unzip windows.zip -d /opt/volatility3/volatility3/symbols/

# Download Linux and Mac symbol packs
wget https://downloads.volatilityfoundation.org/volatility3/symbols/linux.zip
wget https://downloads.volatilityfoundation.org/volatility3/symbols/mac.zip

# Memory acquisition tools (for live systems):
# Windows: winpmem, DumpIt, FTK Imager
# Linux: LiME (Linux Memory Extractor)
sudo insmod lime-$(uname -r).ko "path=/cases/memory/linux_mem.lime format=lime"

# Verify the memory dump
file /cases/case-2024-001/memory/memory.raw
ls -lh /cases/case-2024-001/memory/memory.raw

Step 2: Identify the Operating System Profile

# Run banners plugin to identify the OS
vol -f /cases/case-2024-001/memory/memory.raw banners

# For Windows, identify the OS version
vol -f /cases/case-2024-001/memory/memory.raw windows.info

# Output example:
# Variable        Value
# Kernel Base     0xf8047e200000
# DTB             0x1ad000
# Symbols         ntkrnlmp.pdb/GUID
# Is64Bit         True
# IsPAE           False
# primary layer   Intel32e
# KdVersionBlock  0xf8047ee232c0
# Major/Minor     15.19041
# Machine Type    34404
# KeNumberProcessors 4
# SystemTime      2024-01-18 14:32:15 UTC
# NtBuildLab      19041.1.amd64fre.vb_release.191206-1406
# NtProductType   NtProductWinNt
# NtSystemRoot    C:\WINDOWS
# PE MajorOperatingSystemVersion 10
# PE MinorOperatingSystemVersion 0

# For Linux memory dumps
vol -f /cases/case-2024-001/memory/linux_mem.lime linux.info

Step 3: Enumerate Processes and Detect Anomalies

# List all running processes
vol -f /cases/case-2024-001/memory/memory.raw windows.pslist | tee /cases/case-2024-001/analysis/pslist.txt

# Show process tree (parent-child relationships)
vol -f /cases/case-2024-001/memory/memory.raw windows.pstree | tee /cases/case-2024-001/analysis/pstree.txt

# Detect hidden processes using cross-view analysis
vol -f /cases/case-2024-001/memory/memory.raw windows.psscan | tee /cases/case-2024-001/analysis/psscan.txt

# Compare pslist vs psscan to find hidden processes
diff <(vol -f memory.raw windows.pslist | awk '{print $1}' | sort) \
     <(vol -f memory.raw windows.psscan | awk '{print $1}' | sort)

# List DLLs loaded by a suspicious process (PID 4532)
vol -f /cases/case-2024-001/memory/memory.raw windows.dlllist --pid 4532

# Check for process hollowing and injection
vol -f /cases/case-2024-001/memory/memory.raw windows.malfind | tee /cases/case-2024-001/analysis/malfind.txt

# Dump suspicious process memory for further analysis
vol -f /cases/case-2024-001/memory/memory.raw windows.memmap --pid 4532 --dump \
   -o /cases/case-2024-001/analysis/dumps/

Step 4: Analyze Network Connections and Registry

# List active network connections
vol -f /cases/case-2024-001/memory/memory.raw windows.netscan | tee /cases/case-2024-001/analysis/netscan.txt

# Filter for established connections
vol -f /cases/case-2024-001/memory/memory.raw windows.netscan | grep ESTABLISHED

# Filter for listening ports
vol -f /cases/case-2024-001/memory/memory.raw windows.netscan | grep LISTENING

# Extract network connections with process mapping
vol -f /cases/case-2024-001/memory/memory.raw windows.netstat | tee /cases/case-2024-001/analysis/netstat.txt

# Dump registry hives from memory
vol -f /cases/case-2024-001/memory/memory.raw windows.registry.hivelist

# Extract specific registry keys
vol -f /cases/case-2024-001/memory/memory.raw windows.registry.printkey \
   --key "Software\Microsoft\Windows\CurrentVersion\Run"

# Check services
vol -f /cases/case-2024-001/memory/memory.raw windows.svcscan | tee /cases/case-2024-001/analysis/services.txt

Step 5: Extract Credentials and Sensitive Data

# Dump cached credentials (hashdump)
vol -f /cases/case-2024-001/memory/memory.raw windows.hashdump | tee /cases/case-2024-001/analysis/hashes.txt

# Extract LSA secrets
vol -f /cases/case-2024-001/memory/memory.raw windows.lsadump

# Dump cached domain credentials
vol -f /cases/case-2024-001/memory/memory.raw windows.cachedump

# Search for plaintext strings in process memory
vol -f /cases/case-2024-001/memory/memory.raw windows.strings --pid 4532 \
   | grep -iE '(password|credential|token|api.key)'

# Extract command history from cmd.exe/powershell
vol -f /cases/case-2024-001/memory/memory.raw windows.cmdline | tee /cases/case-2024-001/analysis/cmdline.txt

# Extract environment variables
vol -f /cases/case-2024-001/memory/memory.raw windows.envars --pid 4532

Step 6: Scan for Malware with YARA Rules

# Scan memory with YARA rules
vol -f /cases/case-2024-001/memory/memory.raw yarascan \
   --yara-file /opt/yara-rules/malware_index.yar | tee /cases/case-2024-001/analysis/yara_hits.txt

# Scan specific process memory
vol -f /cases/case-2024-001/memory/memory.raw yarascan \
   --yara-file /opt/yara-rules/apt_rules.yar --pid 4532

# Check loaded kernel modules for rootkits
vol -f /cases/case-2024-001/memory/memory.raw windows.modules | tee /cases/case-2024-001/analysis/modules.txt

# Detect unlinked/hidden modules
vol -f /cases/case-2024-001/memory/memory.raw windows.modscan | tee /cases/case-2024-001/analysis/modscan.txt

# Check for SSDT hooks (System Service Descriptor Table)
vol -f /cases/case-2024-001/memory/memory.raw windows.ssdt | grep -v "ntoskrnl\|win32k"

# Dump a suspicious executable from memory
vol -f /cases/case-2024-001/memory/memory.raw windows.dumpfiles --pid 4532 \
   -o /cases/case-2024-001/analysis/extracted/

Step 7: Compile Findings into a Report

# Generate comprehensive analysis summary
echo "=== MEMORY FORENSICS REPORT ===" > /cases/case-2024-001/analysis/memory_report.txt
echo "Image: memory.raw" >> /cases/case-2024-001/analysis/memory_report.txt
echo "OS: Windows 10 Build 19041" >> /cases/case-2024-001/analysis/memory_report.txt
echo "" >> /cases/case-2024-001/analysis/memory_report.txt

echo "--- Suspicious Processes ---" >> /cases/case-2024-001/analysis/memory_report.txt
cat /cases/case-2024-001/analysis/malfind.txt >> /cases/case-2024-001/analysis/memory_report.txt

echo "--- Network Connections ---" >> /cases/case-2024-001/analysis/memory_report.txt
cat /cases/case-2024-001/analysis/netscan.txt >> /cases/case-2024-001/analysis/memory_report.txt

echo "--- YARA Matches ---" >> /cases/case-2024-001/analysis/memory_report.txt
cat /cases/case-2024-001/analysis/yara_hits.txt >> /cases/case-2024-001/analysis/memory_report.txt

# Calculate hash of the memory dump for integrity
sha256sum /cases/case-2024-001/memory/memory.raw >> /cases/case-2024-001/analysis/memory_report.txt

Key Concepts

ConceptDescription
Volatile dataInformation that exists only in RAM and is lost when power is removed
Process hollowingTechnique where malware replaces legitimate process memory with malicious code
DLL injectionLoading unauthorized DLLs into a running process address space
EPROCESSWindows kernel structure representing a process; basis for process listing
Pool scanningSearching memory for kernel object signatures to find hidden artifacts
VAD (Virtual Address Descriptor)Memory management structure tracking process virtual memory regions
ISF (Intermediate Symbol Format)Volatility 3 symbol table format for OS-specific structure definitions
MalfindPlugin detecting injected code by examining VAD permissions and content

Tools & Systems

ToolPurpose
Volatility 3Primary open-source memory forensics framework
LiMELinux Memory Extractor for acquiring Linux RAM dumps
WinPmemWindows physical memory acquisition driver
DumpItComae one-click Windows memory dump utility
YARAPattern matching engine for malware signature scanning
RekallAlternative memory forensics framework (Google)
MemProcFSMemory process file system for memory analysis
stringsExtract printable strings from binary memory dumps

Common Scenarios

Scenario 1: Active Malware Investigation Acquire memory with DumpIt, run pslist/pstree to identify suspicious processes, use malfind to detect injected code in svchost.exe, dump the injected memory segment, scan with YARA rules identifying Cobalt Strike beacon, extract C2 IP from netscan, correlate with network logs.

Scenario 2: Credential Theft After Breach Run hashdump and lsadump to extract cached credentials, identify mimikatz execution in cmdline output, check for lsass.exe memory dumps in filesystem artifacts, correlate with lateral movement evidence in network connections.

Scenario 3: Rootkit Detection Compare pslist (uses EPROCESS linked list) with psscan (pool scanning) to find unlinked processes, check modules vs modscan for hidden kernel drivers, examine SSDT for hooks redirecting system calls, dump suspicious modules for static analysis.

Scenario 4: Ransomware Incident Recovery Extract encryption keys from ransomware process memory before system shutdown, identify the ransomware variant using YARA, find the initial execution point through command line artifacts, map lateral movement via network connections.

Output Format

Memory Forensics Analysis:
  Image:            memory.raw (16 GB)
  OS Identified:    Windows 10 x64 Build 19041
  Capture Time:     2024-01-18 14:32:15 UTC

  Process Analysis:
    Total Processes:    87
    Hidden Processes:   2 (PIDs: 4532, 6128)
    Injected Processes: 3 (malfind detections)
    Suspicious:         svchost.exe (PID 4532) - injected code at 0x7FFE0000

  Network Connections:
    Total:        45
    Established:  12
    Suspicious:   3 (C2 connections to 185.xx.xx.xx:443)

  Credentials Found:
    NTLM Hashes:      4 accounts
    Cached Creds:      2 domain accounts

  YARA Matches:
    CobaltStrike_Beacon:  PID 4532 (3 hits)
    Mimikatz_Memory:      PID 6128 (1 hit)

  Extracted Artifacts:   15 files dumped to /analysis/extracted/

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能力 3

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能力 4

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

Codex

36.98%
按下载量换算33

Claude

28.4%
按下载量换算25

Cursor

20.03%
按下载量换算18

Gemini CLI

10.16%
按下载量换算9

安全审计

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Snyk

可疑

权限和风险

敏感数据

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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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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