
Memory Forensics with Volatility
FreeAnalyze RAM dumps for malware and process injection evidence.
Free · Opens the source repo
What Memory Forensics with Volatility does
Conducting memory forensics is a critical skill in incident response, particularly when dealing with malware and process injection. This skill utilizes Volatility 3, a powerful framework for analyzing volatile memory, to extract and analyze evidence from RAM dumps. By capturing and examining the memory of a compromised system, users can uncover signs of malicious activity, including process injection, network connections, and credential theft. This skill is designed for cybersecurity professionals and digital forensics experts who need to perform in-depth analysis of volatile evidence during investigations.
The workflow begins with acquiring a memory image from the target system using tools like WinPmem or Magnet RAM Capture. Once the memory dump is obtained, Volatility 3 helps identify the operating system and analyze running processes, allowing users to detect hidden or suspicious activity. The skill includes commands for listing processes, network connections, and identifying injected code, which are essential for understanding the nature of the compromise.
In addition to process analysis, this skill provides capabilities for extracting sensitive information such as credentials and command line history from memory. Users can generate a structured forensic report that documents all findings, including indicators of compromise and evidence of malware presence. This comprehensive approach ensures that analysts can effectively communicate their findings and support incident response efforts.
Memory forensics is particularly useful in scenarios where traditional disk forensics may fall short, such as during active incidents or when dealing with fileless malware. By leveraging this skill, professionals can enhance their incident response capabilities and improve their understanding of complex security incidents.
When to use it
Use this skill when you need to analyze RAM dumps from systems suspected of being compromised, particularly to detect malware execution or process injection.
When not to use it
Do not use this skill for analyzing disk images or file system artifacts; it is specifically focused on memory forensics.
What you can build with it
Incident Response Analysis
Use this skill to analyze RAM from a compromised endpoint during an active incident to uncover signs of malware.
Malware Investigation
Employ this skill to investigate potential process injections or fileless malware that may only exist in memory.
Credential Theft Confirmation
Utilize this skill to confirm credential theft by analyzing memory for evidence of tools like Mimikatz.
How to install Memory Forensics with Volatility
View source1. Install with the skills CLI
npx skills add mukul975/anthropic-cybersecurity-skills/conducting-memory-forensics-with-volatility --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by mukul975Conducting Memory Forensics with Volatility
When to Use
- An endpoint has been contained during an active incident and volatile evidence must be preserved
- EDR alerts suggest process injection or fileless malware that only exists in memory
- Encryption keys need to be recovered from a ransomware-infected system before shutdown
- Credential theft (Mimikatz, LSASS dumping) is suspected and evidence must be confirmed
- A rootkit or kernel-level compromise is suspected and disk-based analysis is insufficient
Do not use for analyzing disk images or file system artifacts; use disk forensics tools (Autopsy, FTK) for those tasks.
Prerequisites
- Memory acquisition tool deployed or available: WinPmem, Magnet RAM Capture, DumpIt, or AVML (Linux)
- Volatility 3 installed with Python 3.8+ and required symbol tables
- Sufficient storage for memory dumps (equal to system RAM size, typically 8-64 GB)
- YARA rules for malware detection in memory (Florian Roth's signature-base, custom rules)
- Reference baseline of normal processes and DLLs for the OS version being analyzed
- Chain of custody documentation for evidence handling
Workflow
Step 1: Acquire Memory Image
Capture RAM from the target system using a forensically sound method:
Windows (WinPmem):
winpmem_mini_x64.exe output.raw
Windows (Magnet RAM Capture):
MagnetRAMCapture.exe
# GUI-based, select output path, generates .raw file
Windows (DumpIt):
DumpIt.exe
# Creates memory dump in current directory automatically
Linux (AVML - Acquire Volatile Memory for Linux):
./avml output.lime
Document acquisition metadata:
Acquisition Record:
━━━━━━━━━━━━━━━━━
Target Host: WKSTN-042
RAM Size: 16 GB
Dump File: WKSTN-042_20251115_1445.raw
Dump Size: 16,843,612,160 bytes
SHA-256: a4b3c2d1e5f6...
Acquisition Tool: WinPmem 4.0
Acquired By: [Analyst Name]
Timestamp: 2025-11-15T14:45:00Z
Step 2: Identify the Operating System and Profile
Volatility 3 automatically identifies the OS, but verify:
# Get system information
vol -f WKSTN-042_20251115_1445.raw windows.info
# Output includes:
# OS: Windows 10 22H2 (Build 19045.3693)
# Kernel Base: 0xf8066c200000
# DTB: 0x1aa000
# Symbols: ntkrnlmp.pdb
Step 3: Analyze Running Processes
Examine the process tree for suspicious activity:
# List all running processes
vol -f memory.raw windows.pslist
# Show process tree (parent-child relationships)
vol -f memory.raw windows.pstree
# Scan for hidden/unlinked processes (rootkit detection)
vol -f memory.raw windows.psscan
# Compare pslist vs psscan to find hidden processes
# Processes in psscan but NOT in pslist may be hidden by rootkits
Key indicators of compromise in process analysis:
svchost.exerunning without-kparameter or with wrong parent (should beservices.exe)csrss.exeorlsass.exewith abnormal parent process- Processes with misspelled names (
scvhost.exe,lssas.exe) - Unusual processes spawned by
outlook.exe,winword.exe, orexcel.exe - Multiple instances of processes that should be singletons (
lsass.exe,smss.exe)
Step 4: Investigate Network Connections
Extract active and recently closed network connections:
# List all network connections
vol -f memory.raw windows.netscan
# Focus output fields:
# Offset Proto LocalAddr LocalPort ForeignAddr ForeignPort State PID Owner
# 0xe10... TCPv4 10.1.5.42 49721 185.220.101.42 443 ESTAB 3847 update.exe
Cross-reference suspicious connections with the process tree to identify C2 communications. Look for:
- Connections to external IPs from unexpected processes
- High port numbers connecting to port 443/80 from non-browser processes
- Connections from
svchost.exeor system processes to external IPs
Step 5: Detect Process Injection and Malware
Use malfind to identify injected code and memory-resident malware:
# Detect injected code in processes
vol -f memory.raw windows.malfind
# Output shows:
# PID Process Start End Tag Protection Hexdump/Disassembly
# 3847 explorer.exe 0x2a10000 0x2a14000 VadS PAGE_EXECUTE_READWRITE
# MZ header detected - injected PE
# Dump suspicious process memory
vol -f memory.raw windows.memmap --pid 3847 --dump
# List DLLs loaded by a suspicious process
vol -f memory.raw windows.dlllist --pid 3847
# Scan memory with YARA rules
vol -f memory.raw windows.yarascan --yara-file malware_rules.yar
Step 6: Extract Credentials and Artifacts
Recover sensitive data from memory:
# Dump registry hives from memory (for password hash extraction)
vol -f memory.raw windows.registry.hivelist
vol -f memory.raw windows.hashdump
# Extract command line history
vol -f memory.raw windows.cmdline
# List handles (files, registry keys, mutexes)
vol -f memory.raw windows.handles --pid 3847
# Extract clipboard contents
vol -f memory.raw windows.clipboard
# Dump cached files from memory
vol -f memory.raw windows.dumpfiles --pid 3847
Step 7: Generate Forensic Report
Compile findings into a structured analysis report documenting all evidence extracted from memory:
- Process anomalies with PIDs, parent processes, and timestamps
- Network connections with associated process context
- Injected code regions with memory protection flags
- Extracted IOCs (hashes, IPs, domains, mutexes, registry keys)
- YARA rule matches with rule names and match offsets
- Credential exposure (hashes found, accounts at risk)
Key Concepts
| Term | Definition |
|---|---|
| Volatile Evidence | Data that exists only in RAM and is lost when a system is powered off; includes running processes, network connections, encryption keys |
| Process Injection | Technique where malware inserts code into a legitimate process's memory space to evade detection (malfind detects this) |
| EPROCESS | Windows kernel data structure representing a process; psscan searches for these structures even when unlinked from the active process list |
| VAD (Virtual Address Descriptor) | Windows kernel structure tracking memory regions allocated to a process; malfind examines VADs for executable but non-file-backed regions |
| Symbol Tables | OS-specific data structures that Volatility 3 uses to parse memory; downloaded automatically based on detected OS version |
| PAGE_EXECUTE_READWRITE | Memory protection flag indicating a region is readable, writable, and executable; common indicator of injected malicious code |
| Memory-Resident Malware | Malware that operates entirely in RAM without writing persistent files to disk, making it invisible to traditional disk-based antivirus |
Tools & Systems
- Volatility 3: Primary open-source memory forensics framework; Python 3 rewrite with automatic symbol resolution
- WinPmem / DumpIt / Magnet RAM Capture: Memory acquisition tools for Windows systems
- AVML (Acquire Volatile Memory for Linux): Microsoft's open-source Linux memory acquisition tool
- YARA: Pattern matching engine for scanning memory dumps against malware signatures and behavioral rules
- MemProcFS: Memory analysis tool that presents memory as a virtual file system for intuitive browsing
Common Scenarios
Scenario: Detecting Cobalt Strike Beacon in Memory
Context: EDR detects suspicious named pipe activity but cannot identify the source. A memory dump is acquired from the suspect endpoint for analysis.
Approach:
- Run
windows.pstreeto identify the process hierarchy and spot abnormal parent-child relationships - Run
windows.malfindto detect injected code regions, particularly insvchost.exeorrundll32.exe - Dump the injected memory region and scan with YARA rules for Cobalt Strike beacon signatures
- Run
windows.netscanto identify C2 connections and correlate with the injected process PID - Extract the beacon configuration (C2 URLs, sleep time, jitter, watermark) using CobaltStrikeParser
- Run
windows.cmdlineto identify any post-exploitation commands executed
Pitfalls:
- Analyzing only the process list without running malfind (missing injected code in legitimate processes)
- Not capturing memory before isolating the endpoint (EDR containment may trigger malware self-deletion)
- Using Volatility 2 profiles instead of Volatility 3 automatic symbol resolution on newer Windows versions
Output Format
MEMORY FORENSICS ANALYSIS REPORT
==================================
Incident: INC-2025-1547
Evidence File: WKSTN-042_20251115_1445.raw
SHA-256: a4b3c2d1e5f6...
OS Identified: Windows 10 22H2 (Build 19045)
Analysis Tool: Volatility 3.2.0
PROCESS ANOMALIES
PID Process Parent Anomaly
3847 update.exe powershell Suspicious executable in Temp directory
5102 svchost.exe explorer Wrong parent (expected services.exe)
--- [hidden] --- Found in psscan but not pslist
INJECTED CODE
PID Process Address Range Protection Finding
5102 svchost.exe 0x00A10000-0x00A14 PAGE_EXECUTE_READWRITE MZ header (PE injection)
NETWORK CONNECTIONS
PID Process Local Foreign State
3847 update.exe 10.1.5.42:49721 185.220.101.42:443 ESTABLISHED
5102 svchost.exe 10.1.5.42:51003 91.215.85.17:8443 ESTABLISHED
YARA MATCHES
Rule: CobaltStrike_Beacon_x64
Match PID: 5102 (svchost.exe)
Offset: 0x00A10240
EXTRACTED IOCS
Hashes: [SHA-256 of dumped injected code]
C2 IPs: 185.220.101.42, 91.215.85.17
C2 Domains: [extracted from beacon config]
Mutexes: Global\MSCTF.Shared.MUTEX.ZRQ
Frequently asked questions about Memory Forensics with Volatility
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