memory-forensics▌
sickn33/antigravity-awesome-skills · updated Apr 8, 2026
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Comprehensive techniques for acquiring, analyzing, and extracting artifacts from memory dumps for incident response and malware analysis.
Memory Forensics
Comprehensive techniques for acquiring, analyzing, and extracting artifacts from memory dumps for incident response and malware analysis.
Use this skill when
- Working on memory forensics tasks or workflows
- Needing guidance, best practices, or checklists for memory forensics
Do not use this skill when
- The task is unrelated to memory forensics
- You need a different domain or tool outside this scope
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.
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
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
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 LastContiguousPteHow to use memory-forensics on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add memory-forensics
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches memory-forensics from GitHub repository sickn33/antigravity-awesome-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate memory-forensics. Access the skill through slash commands (e.g., /memory-forensics) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
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Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★61 reviews- ★★★★★Mateo Iyer· Dec 28, 2024
memory-forensics is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Diego Mehta· Dec 20, 2024
Useful defaults in memory-forensics — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Mei Dixit· Dec 12, 2024
Keeps context tight: memory-forensics is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Advait Mensah· Dec 12, 2024
Registry listing for memory-forensics matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Dhruvi Jain· Dec 8, 2024
Registry listing for memory-forensics matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Oshnikdeep· Nov 27, 2024
memory-forensics reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Charlotte Abebe· Nov 27, 2024
memory-forensics has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Advait Okafor· Nov 19, 2024
Solid pick for teams standardizing on skills: memory-forensics is focused, and the summary matches what you get after install.
- ★★★★★Mei Bhatia· Nov 7, 2024
memory-forensics has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Soo Agarwal· Nov 3, 2024
I recommend memory-forensics for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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