Memory Forensics

Memory Forensics

Overview

This public intake copy packages plugins/antigravity-awesome-skills-claude/skills/memory-forensics from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

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

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Memory Acquisition, Volatility 3 Framework, Data Structures, Detection Patterns, YARA Integration, String Analysis.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• Working on memory forensics tasks or workflows
• Needing guidance, best practices, or checklists for memory forensics
• The task is unrelated to memory forensics
• You need a different domain or tool outside this scope
• Use when the request clearly matches the imported source intent: Comprehensive techniques for acquiring, analyzing, and extracting artifacts from memory dumps for incident response and malware analysis.
• Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Clarify goals, constraints, and required inputs.
2. Apply relevant best practices and validate outcomes.
3. Provide actionable steps and verification.
4. If detailed examples are required, open resources/implementation-playbook.md.
5. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
6. Read the overview and provenance files before loading any copied upstream support files.
7. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.

Imported Workflow Notes

Imported: Instructions

• Clarify goals, constraints, and required inputs.
• Apply relevant best practices and validate outcomes.
• Provide actionable steps and verification.
• If detailed examples are required, open resources/implementation-playbook.md.

Imported: 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"

Imported: 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

Examples

Example 1: Ask for the upstream workflow directly

Use @memory-forensics to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @memory-forensics against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @memory-forensics for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @memory-forensics using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Minimize footprint: Use lightweight acquisition tools
• Document everything: Record time, tool, and hash of capture
• Verify integrity: Hash memory dump immediately after capture
• Chain of custody: Maintain proper forensic handling
• Start broad: Get overview before deep diving
• Cross-reference: Use multiple plugins for same data
• Timeline correlation: Correlate memory findings with disk/network

Imported Operating Notes

Imported: 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

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills-claude/skills/memory-forensics, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

Imported Reference Notes

Imported: Volatility 3 Framework

Installation and Setup

# 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

Essential Plugins

Process Analysis

# 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 Analysis

# Network connections
vol -f memory.raw windows.netscan

# Network connection state
vol -f memory.raw windows.netstat

DLL and Module Analysis

# 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>

Memory Injection Detection

# 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

Registry Analysis

# 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

File System Artifacts

# 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

Linux Analysis

# 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

macOS Analysis

# 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

Imported: 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

Imported: 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

Imported: 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

Imported: 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

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.