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Agent Skill · 研究检索

conducting-memory-forensics-with-volatility(进行具有波动性的内存取证)

conducting-memory-forensics-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。

conducting-memory-forensics-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,权限为操作浏览器;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 58,406。

总安装 416周安装 17GitHub Stars 5,875下载 135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:conducting-memory-forensics-with-volatility(进行具有波动性的内存取证)
来源仓库:https://github.com/mukul975/anthropic-cybersecurity-skills
仓库路径:skills/conducting-memory-forensics-with-volatility
安装命令:
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill conducting-memory-forensics-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 conducting-memory-forensics-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。

用于在内存中提取和分析易失性证据,适用于事件响应和密码恢复场景。适合处理进程注入、无文件恶意软件或凭证转储等内存级威胁分析。通过命令行工具执行内存取证流程,需配合 Volatility 框架使用。安装前请确认系统权限及是否允许运行内存分析命令,避免影响生产环境。

conducting-memory-forensics-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/conducting-memory-forensics-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

    它需要操作浏览器,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

conducting-memory-forensics-with-volatility 怎么安装?

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

conducting-memory-forensics-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。

conducting-memory-forensics-with-volatility 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

conducting-memory-forensics-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。

conducting-memory-forensics-with-volatility 用的人多吗?

公开数据是累计安装 416 次,近一周安装 17 次,下载 135 次,GitHub 5,875 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。

conducting-memory-forensics-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 5,875 星,维护活跃度相对可查。

先想清楚的地方

  • 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

  • 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
conducting-memory-forensics-with-volatility

进行具有波动性的内存取证 · 本页

4165,875操作浏览器未明确未通过

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

Conducting Memory Forensics with Volatility

When to Use

  • An endpoint has been contained during an active incident and volatile evidence must be preserved
  • EDR alerts suggest process injection or fileless malware that only exists in memory
  • Encryption keys need to be recovered from a ransomware-infected system before shutdown
  • Credential theft (Mimikatz, LSASS dumping) is suspected and evidence must be confirmed
  • A rootkit or kernel-level compromise is suspected and disk-based analysis is insufficient

Do not use for analyzing disk images or file system artifacts; use disk forensics tools (Autopsy, FTK) for those tasks.

Prerequisites

  • Memory acquisition tool deployed or available: WinPmem, Magnet RAM Capture, DumpIt, or AVML (Linux)
  • Volatility 3 installed with Python 3.8+ and required symbol tables
  • Sufficient storage for memory dumps (equal to system RAM size, typically 8-64 GB)
  • YARA rules for malware detection in memory (Florian Roth's signature-base, custom rules)
  • Reference baseline of normal processes and DLLs for the OS version being analyzed
  • Chain of custody documentation for evidence handling

Workflow

Step 1: Acquire Memory Image

Capture RAM from the target system using a forensically sound method:

Windows (WinPmem):

winpmem_mini_x64.exe output.raw

Windows (Magnet RAM Capture):

MagnetRAMCapture.exe
# GUI-based, select output path, generates .raw file

Windows (DumpIt):

DumpIt.exe
# Creates memory dump in current directory automatically

Linux (AVML - Acquire Volatile Memory for Linux):

./avml output.lime

Document acquisition metadata:

Acquisition Record:
━━━━━━━━━━━━━━━━━
Target Host:      WKSTN-042
RAM Size:         16 GB
Dump File:        WKSTN-042_20251115_1445.raw
Dump Size:        16,843,612,160 bytes
SHA-256:          a4b3c2d1e5f6...
Acquisition Tool: WinPmem 4.0
Acquired By:      [Analyst Name]
Timestamp:        2025-11-15T14:45:00Z

Step 2: Identify the Operating System and Profile

Volatility 3 automatically identifies the OS, but verify:

# Get system information
vol -f WKSTN-042_20251115_1445.raw windows.info

# Output includes:
# OS: Windows 10 22H2 (Build 19045.3693)
# Kernel Base: 0xf8066c200000
# DTB: 0x1aa000
# Symbols: ntkrnlmp.pdb

Step 3: Analyze Running Processes

Examine the process tree for suspicious activity:

# List all running processes
vol -f memory.raw windows.pslist

# Show process tree (parent-child relationships)
vol -f memory.raw windows.pstree

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

# Compare pslist vs psscan to find hidden processes
# Processes in psscan but NOT in pslist may be hidden by rootkits

Key indicators of compromise in process analysis:

  • svchost.exe running without -k parameter or with wrong parent (should be services.exe)
  • csrss.exe or lsass.exe with abnormal parent process
  • Processes with misspelled names (scvhost.exe, lssas.exe)
  • Unusual processes spawned by outlook.exe, winword.exe, or excel.exe
  • Multiple instances of processes that should be singletons (lsass.exe, smss.exe)

Step 4: Investigate Network Connections

Extract active and recently closed network connections:

# List all network connections
vol -f memory.raw windows.netscan

# Focus output fields:
# Offset    Proto  LocalAddr     LocalPort  ForeignAddr    ForeignPort  State     PID  Owner
# 0xe10...  TCPv4  10.1.5.42     49721     185.220.101.42  443         ESTAB     3847  update.exe

Cross-reference suspicious connections with the process tree to identify C2 communications. Look for:

  • Connections to external IPs from unexpected processes
  • High port numbers connecting to port 443/80 from non-browser processes
  • Connections from svchost.exe or system processes to external IPs

Step 5: Detect Process Injection and Malware

Use malfind to identify injected code and memory-resident malware:

# Detect injected code in processes
vol -f memory.raw windows.malfind

# Output shows:
# PID  Process       Start      End        Tag  Protection  Hexdump/Disassembly
# 3847 explorer.exe  0x2a10000  0x2a14000  VadS PAGE_EXECUTE_READWRITE
# MZ header detected - injected PE

# Dump suspicious process memory
vol -f memory.raw windows.memmap --pid 3847 --dump

# List DLLs loaded by a suspicious process
vol -f memory.raw windows.dlllist --pid 3847

# Scan memory with YARA rules
vol -f memory.raw windows.yarascan --yara-file malware_rules.yar

Step 6: Extract Credentials and Artifacts

Recover sensitive data from memory:

# Dump registry hives from memory (for password hash extraction)
vol -f memory.raw windows.registry.hivelist
vol -f memory.raw windows.hashdump

# Extract command line history
vol -f memory.raw windows.cmdline

# List handles (files, registry keys, mutexes)
vol -f memory.raw windows.handles --pid 3847

# Extract clipboard contents
vol -f memory.raw windows.clipboard

# Dump cached files from memory
vol -f memory.raw windows.dumpfiles --pid 3847

Step 7: Generate Forensic Report

Compile findings into a structured analysis report documenting all evidence extracted from memory:

  • Process anomalies with PIDs, parent processes, and timestamps
  • Network connections with associated process context
  • Injected code regions with memory protection flags
  • Extracted IOCs (hashes, IPs, domains, mutexes, registry keys)
  • YARA rule matches with rule names and match offsets
  • Credential exposure (hashes found, accounts at risk)

Key Concepts

TermDefinition
Volatile EvidenceData that exists only in RAM and is lost when a system is powered off; includes running processes, network connections, encryption keys
Process InjectionTechnique where malware inserts code into a legitimate process's memory space to evade detection (malfind detects this)
EPROCESSWindows kernel data structure representing a process; psscan searches for these structures even when unlinked from the active process list
VAD (Virtual Address Descriptor)Windows kernel structure tracking memory regions allocated to a process; malfind examines VADs for executable but non-file-backed regions
Symbol TablesOS-specific data structures that Volatility 3 uses to parse memory; downloaded automatically based on detected OS version
PAGE_EXECUTE_READWRITEMemory protection flag indicating a region is readable, writable, and executable; common indicator of injected malicious code
Memory-Resident MalwareMalware that operates entirely in RAM without writing persistent files to disk, making it invisible to traditional disk-based antivirus

Tools & Systems

  • Volatility 3: Primary open-source memory forensics framework; Python 3 rewrite with automatic symbol resolution
  • WinPmem / DumpIt / Magnet RAM Capture: Memory acquisition tools for Windows systems
  • AVML (Acquire Volatile Memory for Linux): Microsoft's open-source Linux memory acquisition tool
  • YARA: Pattern matching engine for scanning memory dumps against malware signatures and behavioral rules
  • MemProcFS: Memory analysis tool that presents memory as a virtual file system for intuitive browsing

Common Scenarios

Scenario: Detecting Cobalt Strike Beacon in Memory

Context: EDR detects suspicious named pipe activity but cannot identify the source. A memory dump is acquired from the suspect endpoint for analysis.

Approach:

  1. Run windows.pstree to identify the process hierarchy and spot abnormal parent-child relationships
  2. Run windows.malfind to detect injected code regions, particularly in svchost.exe or rundll32.exe
  3. Dump the injected memory region and scan with YARA rules for Cobalt Strike beacon signatures
  4. Run windows.netscan to identify C2 connections and correlate with the injected process PID
  5. Extract the beacon configuration (C2 URLs, sleep time, jitter, watermark) using CobaltStrikeParser
  6. Run windows.cmdline to identify any post-exploitation commands executed

Pitfalls:

  • Analyzing only the process list without running malfind (missing injected code in legitimate processes)
  • Not capturing memory before isolating the endpoint (EDR containment may trigger malware self-deletion)
  • Using Volatility 2 profiles instead of Volatility 3 automatic symbol resolution on newer Windows versions

Output Format

MEMORY FORENSICS ANALYSIS REPORT
==================================
Incident:         INC-2025-1547
Evidence File:    WKSTN-042_20251115_1445.raw
SHA-256:          a4b3c2d1e5f6...
OS Identified:    Windows 10 22H2 (Build 19045)
Analysis Tool:    Volatility 3.2.0

PROCESS ANOMALIES
PID    Process         Parent       Anomaly
3847   update.exe      powershell   Suspicious executable in Temp directory
5102   svchost.exe     explorer     Wrong parent (expected services.exe)
---    [hidden]        ---          Found in psscan but not pslist

INJECTED CODE
PID    Process        Address Range        Protection              Finding
5102   svchost.exe    0x00A10000-0x00A14   PAGE_EXECUTE_READWRITE  MZ header (PE injection)

NETWORK CONNECTIONS
PID    Process      Local              Foreign             State
3847   update.exe   10.1.5.42:49721    185.220.101.42:443  ESTABLISHED
5102   svchost.exe  10.1.5.42:51003    91.215.85.17:8443   ESTABLISHED

YARA MATCHES
Rule: CobaltStrike_Beacon_x64
Match PID: 5102 (svchost.exe)
Offset: 0x00A10240

EXTRACTED IOCS
Hashes:     [SHA-256 of dumped injected code]
C2 IPs:     185.220.101.42, 91.215.85.17
C2 Domains: [extracted from beacon config]
Mutexes:    Global\MSCTF.Shared.MUTEX.ZRQ

平台分布

Codex

34.84%
按下载量换算47

Claude

28.95%
按下载量换算39

Cursor

17.77%
按下载量换算24

Gemini CLI

9.12%
按下载量换算12

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

未通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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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