Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
日本語の概要は準備中です。原文の説明を表示しています。
Master memory forensics techniques including memory acquisition, process analysis, and artifact extraction using Volatility and related tools. Use when analyzing memory dumps, investigating incidents, or performing malware analysis from RAM captures.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
AUTHORIZED USE ONLY: These skills are for DEFENSIVE security analysis and authorized research:
NEVER use for:
Comprehensive techniques for acquiring, analyzing, and extracting artifacts from memory dumps for incident response and malware analysis.
# WinPmem (Recommended)
winpmem_mini_x64.exe memory.raw
# DumpIt
DumpIt.exe
# Belkasoft RAM Capturer
# GUI-based, outputs raw format
# Magnet RAM Capture
# GUI-based, outputs raw format
# LiME (Linux Memory Extractor)
sudo insmod lime.ko "path=/tmp/memory.lime format=lime"
# /dev/mem (limited, requires permissions)
sudo dd if=/dev/mem of=memory.raw bs=1M
# /proc/kcore (ELF format)
sudo cp /proc/kcore memory.elf
# osxpmem
sudo ./osxpmem -o memory.raw
# MacQuisition (commercial)
# VMware: .vmem file is raw memory
cp vm.vmem memory.raw
# VirtualBox: Use debug console
vboxmanage debugvm "VMName" dumpvmcore --filename memory.elf
# QEMU
virsh dump <domain> memory.raw --memory-only
# Hyper-V
# Checkpoint contains memory state
# Install Volatility 3
pip install volatility3
# Install symbol tables (Windows)
# Download from https://downloads.volatilityfoundation.org/volatility3/symbols/
# Basic usage
vol -f memory.raw <plugin>
# With symbol path
vol -f memory.raw -s /path/to/symbols windows.pslist
# List processes
vol -f memory.raw windows.pslist
# Process tree (parent-child relationships)
vol -f memory.raw windows.pstree
# Hidden process detection
vol -f memory.raw windows.psscan
# Process memory dumps
vol -f memory.raw windows.memmap --pid <PID> --dump
# Process environment variables
vol -f memory.raw windows.envars --pid <PID>
# Command line arguments
vol -f memory.raw windows.cmdline
# Network connections
vol -f memory.raw windows.netscan
# Network connection state
vol -f memory.raw windows.netstat
# Loaded DLLs per process
vol -f memory.raw windows.dlllist --pid <PID>
# Find hidden/injected DLLs
vol -f memory.raw windows.ldrmodules
# Kernel modules
vol -f memory.raw windows.modules
# Module dumps
vol -f memory.raw windows.moddump --pid <PID>
# Detect code injection
vol -f memory.raw windows.malfind
# VAD (Virtual Address Descriptor) analysis
vol -f memory.raw windows.vadinfo --pid <PID>
# Dump suspicious memory regions
vol -f memory.raw windows.vadyarascan --yara-rules rules.yar
# List registry hives
vol -f memory.raw windows.registry.hivelist
# Print registry key
vol -f memory.raw windows.registry.printkey --key "Software\Microsoft\Windows\CurrentVersion\Run"
# Dump registry hive
vol -f memory.raw windows.registry.hivescan --dump
# Scan for file objects
vol -f memory.raw windows.filescan
# Dump files from memory
vol -f memory.raw windows.dumpfiles --pid <PID>
# MFT analysis
vol -f memory.raw windows.mftscan
# Process listing
vol -f memory.raw linux.pslist
# Process tree
vol -f memory.raw linux.pstree
# Bash history
vol -f memory.raw linux.bash
# Network connections
vol -f memory.raw linux.sockstat
# Loaded kernel modules
vol -f memory.raw linux.lsmod
# Mount points
vol -f memory.raw linux.mount
# Environment variables
vol -f memory.raw linux.envars
# Process listing
vol -f memory.raw mac.pslist
# Process tree
vol -f memory.raw mac.pstree
# Network connections
vol -f memory.raw mac.netstat
# Kernel extensions
vol -f memory.raw mac.lsmod
# 1. Initial process survey
vol -f memory.raw windows.pstree > processes.txt
vol -f memory.raw windows.pslist > pslist.txt
# 2. Network connections
vol -f memory.raw windows.netscan > network.txt
# 3. Detect injection
vol -f memory.raw windows.malfind > malfind.txt
# 4. Analyze suspicious processes
vol -f memory.raw windows.dlllist --pid <PID>
vol -f memory.raw windows.handles --pid <PID>
# 5. Dump suspicious executables
vol -f memory.raw windows.pslist --pid <PID> --dump
# 6. Extract strings from dumps
strings -a pid.<PID>.exe > strings.txt
# 7. YARA scanning
vol -f memory.raw windows.yarascan --yara-rules malware.yar
# 1. Timeline of events
vol -f memory.raw windows.timeliner > timeline.csv
# 2. User activity
vol -f memory.raw windows.cmdline
vol -f memory.raw windows.consoles
# 3. Persistence mechanisms
vol -f memory.raw windows.registry.printkey \
--key "Software\Microsoft\Windows\CurrentVersion\Run"
# 4. Services
vol -f memory.raw windows.svcscan
# 5. Scheduled tasks
vol -f memory.raw windows.scheduled_tasks
# 6. Recent files
vol -f memory.raw windows.filescan | grep -i "recent"
// EPROCESS (Executive Process)
typedef struct _EPROCESS {
KPROCESS Pcb; // Kernel process block
EX_PUSH_LOCK ProcessLock;
LARGE_INTEGER CreateTime;
LARGE_INTEGER ExitTime;
// ...
LIST_ENTRY ActiveProcessLinks; // Doubly-linked list
ULONG_PTR UniqueProcessId; // PID
// ...
PEB* Peb; // Process Environment Block
// ...
} EPROCESS;
// PEB (Process Environment Block)
typedef struct _PEB {
BOOLEAN InheritedAddressSpace;
BOOLEAN ReadImageFileExecOptions;
BOOLEAN BeingDebugged; // Anti-debug check
// ...
PVOID ImageBaseAddress; // Base address of executable
PPEB_LDR_DATA Ldr; // Loader data (DLL list)
PRTL_USER_PROCESS_PARAMETERS ProcessParameters;
// ...
} PEB;
typedef struct _MMVAD {
MMVAD_SHORT Core;
union {
ULONG LongFlags;
MMVAD_FLAGS VadFlags;
} u;
// ...
PVOID FirstPrototypePte;
PVOID LastContiguousPte;
// ...
PFILE_OBJECT FileObject;
} MMVAD;
// Memory protection flags
#define PAGE_EXECUTE 0x10
#define PAGE_EXECUTE_READ 0x20
#define PAGE_EXECUTE_READWRITE 0x40
#define PAGE_EXECUTE_WRITECOPY 0x80
# Malfind indicators
# - PAGE_EXECUTE_READWRITE protection (suspicious)
# - MZ header in non-image VAD region
# - Shellcode patterns at allocation start
# Common injection techniques
# 1. Classic DLL Injection
# - VirtualAllocEx + WriteProcessMemory + CreateRemoteThread
# 2. Process Hollowing
# - CreateProcess (SUSPENDED) + NtUnmapViewOfSection + WriteProcessMemory
# 3. APC Injection
# - QueueUserAPC targeting alertable threads
# 4. Thread Execution Hijacking
# - SuspendThread + SetThreadContext + ResumeThread
# Compare process lists
vol -f memory.raw windows.pslist > pslist.txt
vol -f memory.raw windows.psscan > psscan.txt
diff pslist.txt psscan.txt # Hidden processes
# Check for DKOM (Direct Kernel Object Manipulation)
vol -f memory.raw windows.callbacks
# Detect hooked functions
vol -f memory.raw windows.ssdt # System Service Descriptor Table
# Driver analysis
vol -f memory.raw windows.driverscan
vol -f memory.raw windows.driverirp
# Dump hashes (requires hivelist first)
vol -f memory.raw windows.hashdump
# LSA secrets
vol -f memory.raw windows.lsadump
# Cached domain credentials
vol -f memory.raw windows.cachedump
# Mimikatz-style extraction
# Requires specific plugins/tools
rule Suspicious_Injection
{
meta:
description = "Detects common injection shellcode"
strings:
// Common shellcode patterns
$mz = { 4D 5A }
$shellcode1 = { 55 8B EC 83 EC } // Function prologue
$api_hash = { 68 ?? ?? ?? ?? 68 ?? ?? ?? ?? E8 } // Push hash, call
condition:
$mz at 0 or any of ($shellcode*)
}
rule Cobalt_Strike_Beacon
{
meta:
description = "Detects Cobalt Strike beacon in memory"
strings:
$config = { 00 01 00 01 00 02 }
$sleep = "sleeptime"
$beacon = "%s (admin)" wide
condition:
2 of them
}
# Scan all process memory
vol -f memory.raw windows.yarascan --yara-rules rules.yar
# Scan specific process
vol -f memory.raw windows.yarascan --yara-rules rules.yar --pid 1234
# Scan kernel memory
vol -f memory.raw windows.yarascan --yara-rules rules.yar --kernel
# Basic string extraction
strings -a memory.raw > all_strings.txt
# Unicode strings
strings -el memory.raw >> all_strings.txt
# Targeted extraction from process dump
vol -f memory.raw windows.memmap --pid 1234 --dump
strings -a pid.1234.dmp > process_strings.txt
# Pattern matching
grep -E "(https?://|[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3})" all_strings.txt
# FLOSS extracts obfuscated strings
floss malware.exe > floss_output.txt
# From memory dump
floss pid.1234.dmp
vol -f memory.raw windows.info must confirm OS version before any plugin output is trusted.pslist misses DKOM-hidden processes; cross-validate with psscan and pstree before reporting any process as hidden.| Anti-Pattern | Why It Fails | Correct Approach |
|---|---|---|
| Skipping acquisition hash | Dump integrity cannot be proven in court or peer review; challenges invalidate all findings | Hash immediately: sha256sum memory.raw > memory.raw.sha256 before any analysis |
| Wrong OS profile | Incorrect offsets produce garbage output with no error — findings appear valid but are fabricated | Run vol -f memory.raw windows.info first; confirm OS version and build before other plugins |
| Analyzing on the live suspect system | Tool artifacts contaminate volatile evidence; file timestamps change; live-response tools modify RAM state | Acquire dump, transfer to isolated analysis workstation, analyze the copy only |
| Trusting a single plugin | DKOM rootkits hide from pslist linked-list traversal but appear in psscan pool scan | Cross-validate process lists with at least pslist, psscan, and pstree before reporting |
| Missing timeline correlation | Memory artifacts without disk/network context cannot establish causality or attacker timeline | Correlate memory findings with event logs and PCAP before writing the incident report |
Before starting:
Read .claude/context/memory/learnings.md
After completing:
.claude/context/memory/learnings.md.claude/context/memory/issues.md.claude/context/memory/decisions.mdASSUME INTERRUPTION: If it's not in memory, it didn't happen.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
日本語の概要は準備中です。原文の説明を表示しています。
Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.
日本語の概要は準備中です。原文の説明を表示しています。
N-round opposing-stance debates for trade-off analysis. Assigns pro/con roles to agents, runs structured debate rounds with quality scoring, and produces a moderator synthesis with confidence-rated recommendation. Generalizable to architecture, technology, security, and design decisions.
日本語の概要は準備中です。原文の説明を表示しています。
Force adversarial code review stance that eliminates confirmation bias — reviewer must find issues or re-analyze
日本語の概要は準備中です。原文の説明を表示しています。
Creates specialized AI agents on-demand when no existing agent matches a request. Use when the Router cannot find a suitable agent for a task. Enables self-evolution by generating persistent agents.
日本語の概要は準備中です。原文の説明を表示しています。
LLM-as-judge evaluation framework with 5-dimension rubric (accuracy, groundedness, coherence, completeness, helpfulness) for scoring AI-generated content quality with weighted composite scores and evidence citations
日本語の概要は準備中です。原文の説明を表示しています。