memory-forensics-volatility

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npx skills add yaklang/hack-skills --skill memory-forensics-volatility

Documentation

SKILL.md

npx skills add ...

Documentation

SKILL.md

Memory forensics playbook using Volatility 2/3. Use when analyzing memory dumps for malware analysis, credential extraction, process investigation, code injection detection, and incident response timeline reconstruction.

npx skills add yaklang/hack-skills --skill memory-forensics-volatility

Documentation

SKILL.mdView source

SKILL: Memory Forensics — Expert Analysis Playbook

AI LOAD INSTRUCTION: Expert memory forensics techniques using Volatility 2 and 3. Covers memory acquisition, OS identification, process analysis (hidden process detection), network connections, DLL/module analysis, code injection detection (malfind), credential extraction, file carving, registry analysis, and timeline generation. Base models miss the Vol2/Vol3 command differences, malware indicator patterns, and Linux-specific memory analysis.

Before going deep, consider loading:

traffic-analysis-pcap for correlating network artifacts with memory findings
steganography-techniques if hidden data suspected in extracted files
windows-privilege-escalation for understanding post-exploitation artifacts in memory

Quick Reference

Also load VOLATILITY_CHEATSHEET.md when you need:

Vol2 vs Vol3 command comparison table
Common plugin sequences for specific investigation types

1. MEMORY ACQUISITION

Linux

# LiME (Linux Memory Extractor) — kernel module
insmod lime.ko "path=/tmp/mem.lime format=lime"
 
# /proc/kcore (if available)
dd if=/proc/kcore of=/tmp/mem.raw bs=1M
 
# AVML (Microsoft's open-source)
./avml /tmp/mem.lime

Windows

# WinPmem
winpmem_mini_x64.exe memdump.raw
 
# FTK Imager (GUI) — capture memory to file
 
# DumpIt (single-click memory dump)
DumpIt.exe
 
# Comae (MagnetRAM)
MagnetRAMCapture.exe /output memdump.raw

Virtual Machines

# VMware: .vmem file in VM directory (suspend VM first)
# VirtualBox: VBoxManage debugvm "VM_NAME" dumpvmcore --filename mem.raw
# KVM/QEMU: virsh dump DOMAIN memdump --memory-only
# Hyper-V: checkpoint VM → inspect .bin files

2. VOLATILITY 2 vs 3

Concept	Volatility 2	Volatility 3
Profile system	`--profile=Win10x64_19041`	Auto-detected (symbol tables)
Image info	`imageinfo`	`windows.info` / `linux.info`
Process list	`pslist`	`windows.pslist`
Network	`netscan` / `connections`	`windows.netscan` / `windows.netstat`
DLLs	`dlllist`	`windows.dlllist`
Injection	`malfind`	`windows.malfind`
Hashes	`hashdump`	`windows.hashdump`
Files	`filescan`	`windows.filescan`
Registry	`hivelist` / `printkey`	`windows.registry.hivelist` / `windows.registry.printkey`
Install	`pip2 install volatility`	`pip3 install volatility3`

3. ANALYSIS METHODOLOGY

Step 1: Identify OS

# Vol2
vol.py -f mem.raw imageinfo
vol.py -f mem.raw kdbgscan
 
# Vol3
vol -f mem.raw windows.info
vol -f mem.raw banners.Banners

Step 2: Process Listing — Hidden Process Detection

# Vol2
vol.py -f mem.raw --profile=PROFILE pslist       # EPROCESS linked list
vol.py -f mem.raw --profile=PROFILE psscan       # pool tag scan (finds unlinked)
vol.py -f mem.raw --profile=PROFILE pstree       # parent-child hierarchy
 
# Vol3
vol -f mem.raw windows.pslist
vol -f mem.raw windows.psscan
vol -f mem.raw windows.pstree

Red flags: Process in psscan but not pslist = DKOM (Direct Kernel Object Manipulation) hiding.

Step 3: Network Connections

# Vol2
vol.py -f mem.raw --profile=PROFILE netscan      # TCP/UDP endpoints
vol.py -f mem.raw --profile=PROFILE connections   # XP/2003 only
vol.py -f mem.raw --profile=PROFILE connscan      # closed connections
 
# Vol3
vol -f mem.raw windows.netscan
vol -f mem.raw windows.netstat

Step 4: DLL / Module Analysis

# Vol2
vol.py -f mem.raw --profile=PROFILE dlllist -p PID
vol.py -f mem.raw --profile=PROFILE ldrmodules -p PID   # find unlinked DLLs
 
# Vol3
vol -f mem.raw windows.dlllist --pid PID

Red flags: DLL in dlllist but False in all three ldrmodules columns = reflective DLL injection.

Step 5: Code Injection Detection (Malfind)

# Vol2
vol.py -f mem.raw --profile=PROFILE malfind -p PID
vol.py -f mem.raw --profile=PROFILE malfind -D /tmp/dump/   # dump injected sections
 
# Vol3
vol -f mem.raw windows.malfind --pid PID

What malfind detects: Memory regions with PAGE_EXECUTE_READWRITE that don't map to a file on disk — classic shellcode/injection indicator.

Step 6: Credential Extraction

# Vol2
vol.py -f mem.raw --profile=PROFILE hashdump      # SAM hashes
vol.py -f mem.raw --profile=PROFILE lsadump       # LSA secrets
vol.py -f mem.raw --profile=PROFILE cachedump     # domain cached creds
vol.py -f mem.raw --profile=PROFILE mimikatz      # (plugin) plaintext creds
 
# Vol3
vol -f mem.raw windows.hashdump
vol -f mem.raw windows.lsadump
vol -f mem.raw windows.cachedump

Step 7: File Extraction

# Vol2
vol.py -f mem.raw --profile=PROFILE filescan | grep -i "password\|secret\|flag"
vol.py -f mem.raw --profile=PROFILE dumpfiles -Q OFFSET -D /tmp/dump/
 
# Vol3
vol -f mem.raw windows.filescan
vol -f mem.raw windows.dumpfiles --virtaddr OFFSET

Step 8: Registry Analysis

# Vol2
vol.py -f mem.raw --profile=PROFILE hivelist
vol.py -f mem.raw --profile=PROFILE printkey -K "Software\Microsoft\Windows\CurrentVersion\Run"
vol.py -f mem.raw --profile=PROFILE userassist    # program execution evidence
 
# Vol3
vol -f mem.raw windows.registry.hivelist
vol -f mem.raw windows.registry.printkey --key "Software\Microsoft\Windows\CurrentVersion\Run"

Step 9: Command History

# Vol2
vol.py -f mem.raw --profile=PROFILE cmdscan       # cmd.exe history
vol.py -f mem.raw --profile=PROFILE consoles       # full console output
 
# Vol3
vol -f mem.raw windows.cmdline

Step 10: Timeline Generation

# Vol2
vol.py -f mem.raw --profile=PROFILE timeliner --output=body --output-file=timeline.body
mactime -b timeline.body -d > timeline.csv
 
# Vol3
vol -f mem.raw timeliner.Timeliner

4. LINUX MEMORY ANALYSIS

# Vol2 (requires Linux profile)
vol.py -f mem.lime --profile=LinuxProfile linux_pslist
vol.py -f mem.lime --profile=LinuxProfile linux_pstree
vol.py -f mem.lime --profile=LinuxProfile linux_netstat
vol.py -f mem.lime --profile=LinuxProfile linux_bash        # bash history
vol.py -f mem.lime --profile=LinuxProfile linux_enumerate_files
vol.py -f mem.lime --profile=LinuxProfile linux_proc_maps -p PID
vol.py -f mem.lime --profile=LinuxProfile linux_malfind
 
# Vol3
vol -f mem.lime linux.pslist
vol -f mem.lime linux.pstree
vol -f mem.lime linux.bash
vol -f mem.lime linux.check_afinfo     # rootkit detection
vol -f mem.lime linux.check_syscall    # syscall hooking
vol -f mem.lime linux.tty_check        # TTY hooking

Building Linux Profiles (Vol2)

cd volatility/tools/linux
make
# Creates module.dwarf + System.map → zip as profile
zip LinuxProfile.zip module.dwarf /boot/System.map-$(uname -r)
# Place in volatility/plugins/overlays/linux/

5. MALWARE INDICATORS IN MEMORY

Indicator	Detection Method	What It Means
Process in psscan but not pslist	Compare pslist vs psscan	DKOM — process hiding
Unexpected parent-child	pstree analysis	e.g., svchost spawned by cmd.exe
MZ header in non-image memory	malfind	Reflective DLL / PE injection
RWX memory without backing file	malfind	Shellcode injection
DLL unlinked from all PEB lists	ldrmodules (all False)	Stealth DLL loading
svchost.exe not child of services.exe	pstree	Fake svchost (malware)
Unusual network connections	netscan + PID correlation	C2 communication
Hooking in SSDT/IDT	ssdt / idt plugins	Rootkit
Modified kernel objects	linux_check_syscall	Linux rootkit

Normal Parent-Child Relationships (Windows)

System (4)
└── smss.exe
    └── csrss.exe
    └── wininit.exe
        └── services.exe
            └── svchost.exe (multiple)
            └── spoolsv.exe
        └── lsass.exe
    └── winlogon.exe
        └── explorer.exe
            └── user applications

6. DECISION TREE

Memory dump acquired — need to analyze
│
├── What OS?
│   ├── Windows → vol imageinfo / windows.info (§3 Step 1)
│   └── Linux → build profile or use Vol3 auto-detect (§4)
│
├── Malware investigation?
│   ├── Check processes: pslist vs psscan (hidden?) (§3 Step 2)
│   ├── Check parent-child: pstree (suspicious spawning?) (§5)
│   ├── Check injections: malfind (RWX memory?) (§3 Step 5)
│   ├── Check DLLs: ldrmodules (unlinked?) (§3 Step 4)
│   ├── Check network: netscan (C2 connections?) (§3 Step 3)
│   └── Extract suspicious files: dumpfiles (§3 Step 7)
│
├── Credential recovery?
│   ├── SAM hashes → hashdump (§3 Step 6)
│   ├── LSA secrets → lsadump (§3 Step 6)
│   ├── Cached domain creds → cachedump (§3 Step 6)
│   └── Plaintext passwords → mimikatz plugin (§3 Step 6)
│
├── Incident timeline?
│   ├── timeliner for comprehensive timeline (§3 Step 10)
│   ├── cmdscan / consoles for command history (§3 Step 9)
│   ├── userassist for program execution (§3 Step 8)
│   └── Cross-reference with PCAP timeline (→ traffic-analysis-pcap)
│
├── CTF / flag hunting?
│   ├── filescan + grep for flag patterns (§3 Step 7)
│   ├── cmdscan for typed flags/passwords (§3 Step 9)
│   ├── Clipboard: clipboard plugin
│   ├── Screenshots: screenshot plugin
│   └── Environment vars: envars plugin
│
└── Linux-specific?
    ├── linux_bash for shell history (§4)
    ├── linux_check_syscall for rootkit (§4)
    └── linux_netstat for connections (§4)

npx skills add yaklang/hack-skills --skill memory-forensics-volatility

Documentation

SKILL.md

npx skills add yaklang/hack-skills --skill memory-forensics-volatility

Documentation

SKILL.mdView source

SKILL: Memory Forensics — Expert Analysis Playbook

AI LOAD INSTRUCTION: Expert memory forensics techniques using Volatility 2 and 3. Covers memory acquisition, OS identification, process analysis (hidden process detection), network connections, DLL/module analysis, code injection detection (malfind), credential extraction, file carving, registry analysis, and timeline generation. Base models miss the Vol2/Vol3 command differences, malware indicator patterns, and Linux-specific memory analysis.

Before going deep, consider loading:

traffic-analysis-pcap for correlating network artifacts with memory findings
steganography-techniques if hidden data suspected in extracted files
windows-privilege-escalation for understanding post-exploitation artifacts in memory

Quick Reference

Also load VOLATILITY_CHEATSHEET.md when you need:

Vol2 vs Vol3 command comparison table
Common plugin sequences for specific investigation types

1. MEMORY ACQUISITION

Linux

# LiME (Linux Memory Extractor) — kernel module
insmod lime.ko "path=/tmp/mem.lime format=lime"
 
# /proc/kcore (if available)
dd if=/proc/kcore of=/tmp/mem.raw bs=1M
 
# AVML (Microsoft's open-source)
./avml /tmp/mem.lime

Windows

# WinPmem
winpmem_mini_x64.exe memdump.raw
 
# FTK Imager (GUI) — capture memory to file
 
# DumpIt (single-click memory dump)
DumpIt.exe
 
# Comae (MagnetRAM)
MagnetRAMCapture.exe /output memdump.raw

Virtual Machines

# VMware: .vmem file in VM directory (suspend VM first)
# VirtualBox: VBoxManage debugvm "VM_NAME" dumpvmcore --filename mem.raw
# KVM/QEMU: virsh dump DOMAIN memdump --memory-only
# Hyper-V: checkpoint VM → inspect .bin files

2. VOLATILITY 2 vs 3

Concept	Volatility 2	Volatility 3
Profile system	`--profile=Win10x64_19041`	Auto-detected (symbol tables)
Image info	`imageinfo`	`windows.info` / `linux.info`
Process list	`pslist`	`windows.pslist`
Network	`netscan` / `connections`	`windows.netscan` / `windows.netstat`
DLLs	`dlllist`	`windows.dlllist`
Injection	`malfind`	`windows.malfind`
Hashes	`hashdump`	`windows.hashdump`
Files	`filescan`	`windows.filescan`
Registry	`hivelist` / `printkey`	`windows.registry.hivelist` / `windows.registry.printkey`
Install	`pip2 install volatility`	`pip3 install volatility3`

3. ANALYSIS METHODOLOGY

Step 1: Identify OS

# Vol2
vol.py -f mem.raw imageinfo
vol.py -f mem.raw kdbgscan
 
# Vol3
vol -f mem.raw windows.info
vol -f mem.raw banners.Banners

Step 2: Process Listing — Hidden Process Detection

# Vol2
vol.py -f mem.raw --profile=PROFILE pslist       # EPROCESS linked list
vol.py -f mem.raw --profile=PROFILE psscan       # pool tag scan (finds unlinked)
vol.py -f mem.raw --profile=PROFILE pstree       # parent-child hierarchy
 
# Vol3
vol -f mem.raw windows.pslist
vol -f mem.raw windows.psscan
vol -f mem.raw windows.pstree

Red flags: Process in psscan but not pslist = DKOM (Direct Kernel Object Manipulation) hiding.

Step 3: Network Connections

# Vol2
vol.py -f mem.raw --profile=PROFILE netscan      # TCP/UDP endpoints
vol.py -f mem.raw --profile=PROFILE connections   # XP/2003 only
vol.py -f mem.raw --profile=PROFILE connscan      # closed connections
 
# Vol3
vol -f mem.raw windows.netscan
vol -f mem.raw windows.netstat

Step 4: DLL / Module Analysis

# Vol2
vol.py -f mem.raw --profile=PROFILE dlllist -p PID
vol.py -f mem.raw --profile=PROFILE ldrmodules -p PID   # find unlinked DLLs
 
# Vol3
vol -f mem.raw windows.dlllist --pid PID

Red flags: DLL in dlllist but False in all three ldrmodules columns = reflective DLL injection.

Step 5: Code Injection Detection (Malfind)

# Vol2
vol.py -f mem.raw --profile=PROFILE malfind -p PID
vol.py -f mem.raw --profile=PROFILE malfind -D /tmp/dump/   # dump injected sections
 
# Vol3
vol -f mem.raw windows.malfind --pid PID

What malfind detects: Memory regions with PAGE_EXECUTE_READWRITE that don't map to a file on disk — classic shellcode/injection indicator.

Step 6: Credential Extraction

# Vol2
vol.py -f mem.raw --profile=PROFILE hashdump      # SAM hashes
vol.py -f mem.raw --profile=PROFILE lsadump       # LSA secrets
vol.py -f mem.raw --profile=PROFILE cachedump     # domain cached creds
vol.py -f mem.raw --profile=PROFILE mimikatz      # (plugin) plaintext creds
 
# Vol3
vol -f mem.raw windows.hashdump
vol -f mem.raw windows.lsadump
vol -f mem.raw windows.cachedump

Step 7: File Extraction

# Vol2
vol.py -f mem.raw --profile=PROFILE filescan | grep -i "password\|secret\|flag"
vol.py -f mem.raw --profile=PROFILE dumpfiles -Q OFFSET -D /tmp/dump/
 
# Vol3
vol -f mem.raw windows.filescan
vol -f mem.raw windows.dumpfiles --virtaddr OFFSET

Step 8: Registry Analysis

# Vol2
vol.py -f mem.raw --profile=PROFILE hivelist
vol.py -f mem.raw --profile=PROFILE printkey -K "Software\Microsoft\Windows\CurrentVersion\Run"
vol.py -f mem.raw --profile=PROFILE userassist    # program execution evidence
 
# Vol3
vol -f mem.raw windows.registry.hivelist
vol -f mem.raw windows.registry.printkey --key "Software\Microsoft\Windows\CurrentVersion\Run"

Step 9: Command History

# Vol2
vol.py -f mem.raw --profile=PROFILE cmdscan       # cmd.exe history
vol.py -f mem.raw --profile=PROFILE consoles       # full console output
 
# Vol3
vol -f mem.raw windows.cmdline

Step 10: Timeline Generation

# Vol2
vol.py -f mem.raw --profile=PROFILE timeliner --output=body --output-file=timeline.body
mactime -b timeline.body -d > timeline.csv
 
# Vol3
vol -f mem.raw timeliner.Timeliner

4. LINUX MEMORY ANALYSIS

# Vol2 (requires Linux profile)
vol.py -f mem.lime --profile=LinuxProfile linux_pslist
vol.py -f mem.lime --profile=LinuxProfile linux_pstree
vol.py -f mem.lime --profile=LinuxProfile linux_netstat
vol.py -f mem.lime --profile=LinuxProfile linux_bash        # bash history
vol.py -f mem.lime --profile=LinuxProfile linux_enumerate_files
vol.py -f mem.lime --profile=LinuxProfile linux_proc_maps -p PID
vol.py -f mem.lime --profile=LinuxProfile linux_malfind
 
# Vol3
vol -f mem.lime linux.pslist
vol -f mem.lime linux.pstree
vol -f mem.lime linux.bash
vol -f mem.lime linux.check_afinfo     # rootkit detection
vol -f mem.lime linux.check_syscall    # syscall hooking
vol -f mem.lime linux.tty_check        # TTY hooking

Building Linux Profiles (Vol2)

cd volatility/tools/linux
make
# Creates module.dwarf + System.map → zip as profile
zip LinuxProfile.zip module.dwarf /boot/System.map-$(uname -r)
# Place in volatility/plugins/overlays/linux/

5. MALWARE INDICATORS IN MEMORY

Indicator	Detection Method	What It Means
Process in psscan but not pslist	Compare pslist vs psscan	DKOM — process hiding
Unexpected parent-child	pstree analysis	e.g., svchost spawned by cmd.exe
MZ header in non-image memory	malfind	Reflective DLL / PE injection
RWX memory without backing file	malfind	Shellcode injection
DLL unlinked from all PEB lists	ldrmodules (all False)	Stealth DLL loading
svchost.exe not child of services.exe	pstree	Fake svchost (malware)
Unusual network connections	netscan + PID correlation	C2 communication
Hooking in SSDT/IDT	ssdt / idt plugins	Rootkit
Modified kernel objects	linux_check_syscall	Linux rootkit

Normal Parent-Child Relationships (Windows)

System (4)
└── smss.exe
    └── csrss.exe
    └── wininit.exe
        └── services.exe
            └── svchost.exe (multiple)
            └── spoolsv.exe
        └── lsass.exe
    └── winlogon.exe
        └── explorer.exe
            └── user applications

6. DECISION TREE

Memory dump acquired — need to analyze
│
├── What OS?
│   ├── Windows → vol imageinfo / windows.info (§3 Step 1)
│   └── Linux → build profile or use Vol3 auto-detect (§4)
│
├── Malware investigation?
│   ├── Check processes: pslist vs psscan (hidden?) (§3 Step 2)
│   ├── Check parent-child: pstree (suspicious spawning?) (§5)
│   ├── Check injections: malfind (RWX memory?) (§3 Step 5)
│   ├── Check DLLs: ldrmodules (unlinked?) (§3 Step 4)
│   ├── Check network: netscan (C2 connections?) (§3 Step 3)
│   └── Extract suspicious files: dumpfiles (§3 Step 7)
│
├── Credential recovery?
│   ├── SAM hashes → hashdump (§3 Step 6)
│   ├── LSA secrets → lsadump (§3 Step 6)
│   ├── Cached domain creds → cachedump (§3 Step 6)
│   └── Plaintext passwords → mimikatz plugin (§3 Step 6)
│
├── Incident timeline?
│   ├── timeliner for comprehensive timeline (§3 Step 10)
│   ├── cmdscan / consoles for command history (§3 Step 9)
│   ├── userassist for program execution (§3 Step 8)
│   └── Cross-reference with PCAP timeline (→ traffic-analysis-pcap)
│
├── CTF / flag hunting?
│   ├── filescan + grep for flag patterns (§3 Step 7)
│   ├── cmdscan for typed flags/passwords (§3 Step 9)
│   ├── Clipboard: clipboard plugin
│   ├── Screenshots: screenshot plugin
│   └── Environment vars: envars plugin
│
└── Linux-specific?
    ├── linux_bash for shell history (§4)
    ├── linux_check_syscall for rootkit (§4)
    └── linux_netstat for connections (§4)

memory-forensics-volatility

Documentation

Documentation

memory-forensics-volatility

Documentation

SKILL: Memory Forensics — Expert Analysis Playbook

0. RELATED ROUTING

Quick Reference

1. MEMORY ACQUISITION

Linux

Windows

Virtual Machines

2. VOLATILITY 2 vs 3

3. ANALYSIS METHODOLOGY

Step 1: Identify OS

Step 2: Process Listing — Hidden Process Detection

Step 3: Network Connections

Step 4: DLL / Module Analysis

Step 5: Code Injection Detection (Malfind)

Step 6: Credential Extraction

Step 7: File Extraction

Step 8: Registry Analysis

Step 9: Command History

Step 10: Timeline Generation

4. LINUX MEMORY ANALYSIS

Building Linux Profiles (Vol2)

5. MALWARE INDICATORS IN MEMORY

Normal Parent-Child Relationships (Windows)

6. DECISION TREE

Documentation

Documentation

SKILL: Memory Forensics — Expert Analysis Playbook

0. RELATED ROUTING

Quick Reference

1. MEMORY ACQUISITION

Linux

Windows

Virtual Machines

2. VOLATILITY 2 vs 3

3. ANALYSIS METHODOLOGY

Step 1: Identify OS

Step 2: Process Listing — Hidden Process Detection

Step 3: Network Connections

Step 4: DLL / Module Analysis

Step 5: Code Injection Detection (Malfind)

Step 6: Credential Extraction

Step 7: File Extraction

Step 8: Registry Analysis

Step 9: Command History

Step 10: Timeline Generation

4. LINUX MEMORY ANALYSIS

Building Linux Profiles (Vol2)

5. MALWARE INDICATORS IN MEMORY

Normal Parent-Child Relationships (Windows)

6. DECISION TREE