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memory-forensics

Master memory forensics techniques including memory acquisition, process analysis, and artifact extraction using Volatility and related tools

Install / Use

npx skills add wshobson/agents --skill memory-forensics

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

98/100

Supported Platforms

Universal

Tags

Our assessment of memory-forensics

memory-forensics scores 98/100 on our quality scale, 60th of 1,753 Development & Engineering skills we index (top 4%).

Its SKILL.md is 8.2 KB long, well organised into 89 sections with 15 code examples: a thorough specification that gives an agent plenty to work with.

With 39,920 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
20/20
Description
15/15
Adoption
20/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 4 days ago, so memory-forensics is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-09-25. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

memory-forensics compared with similar skills

All 4 of these similar skills score higher than memory-forensics; compare them before choosing.

SkillScoreStarsUpdatedFormat
memory-forensics (this skill)by wshobson9839.9k4d agoSKILL.md
ai-job-searchby MadsLorentzen10043.9k4d agoCLAUDE.md
claude-howtoby luongnv8910041.7k5d agoCLAUDE.md
algorithmic-artby anthropics100177.9k2d agoSKILL.md
pptxby anthropics100177.9k2d agoSKILL.md

Frequently asked questions

How do I install memory-forensics?
Run npx skills add wshobson/agents --skill memory-forensics. The install tabs above show the steps for each supported agent.
Which AI agents does memory-forensics work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is memory-forensics safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is memory-forensics still maintained?
The repository was last updated 4 days ago, so memory-forensics is actively maintained.

name: memory-forensics description: 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.

Memory Forensics

Comprehensive techniques for acquiring, analyzing, and extracting artifacts from memory dumps for incident response and malware analysis.

When to Use This Skill

  • Performing memory analysis during incident response or breach investigation
  • Extracting malware artifacts (processes, injected code, network connections) from a RAM capture
  • Acquiring volatile memory from a live Windows/Linux/macOS system before shutdown
  • Using Volatility 3 / Rekall to triage memory dumps
  • Recovering credentials, browser sessions, or open files from process memory

Memory Acquisition

Live Acquisition Tools

Windows

# 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

Linux

# 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

macOS

# osxpmem
sudo ./osxpmem -o memory.raw

# MacQuisition (commercial)

Virtual Machine Memory

# 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

Detailed section: Volatility 3 Framework

Originally a 2680-byte section in this SKILL.md. Moved to references/details.md to fit Codex's 8 KB skill body cap.

Analysis Workflows

Malware Analysis Workflow

# 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

Incident Response Workflow

# 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"

Data Structures

Windows Process Structures

// 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;

VAD (Virtual Address Descriptor)

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

Detection Patterns

Process Injection Indicators

# 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

Rootkit Detection

# 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

Credential Extraction

# 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

YARA Integration

Writing Memory YARA Rules

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
}

Scanning Memory

# 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

String Analysis

Extracting Strings

# 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 for Obfuscated Strings

# FLOSS extracts obfuscated strings
floss malware.exe > floss_output.txt

# From memory dump
floss pid.1234.dmp

Best Practices

Acquisition Best Practices

  1. Minimize footprint: Use lightweight acquisition tools
  2. Document everything: Record time, tool, and hash of capture
  3. Verify integrity: Hash memory dump immediately after capture
  4. Chain of custody: Maintain proper forensic handling

Analysis Best Practices

  1. Start broad: Get overview before deep diving
  2. Cross-reference: Use multiple plugins for same data
  3. Timeline correlation: Correlate memory findings with disk/network
  4. Document findings: Keep detailed notes and screenshots
  5. Validate results: Verify findings through multiple methods

Common Pitfalls

  • Stale data: Memory is volatile, analyze promptly
  • Incomplete dumps: Verify dump size matches expected RAM
  • Symbol issues: Ensure correct symbol files for OS version
  • Smear: Memory may change during acquisition
  • Encryption: Some data may be encrypted in memory

Related Skills

View on GitHub
GitHub Stars39.9k
CategoryDevelopment
Updated4d ago
Forks4.3k

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions