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Volatility

Volatility is one of the most powerful and widely used memory forensics frameworks. It allows investigators to analyze RAM dumps from Windows, Linux, macOS, and Android systems to uncover volatile evidence such as running processes, network connections, injected code, malware activity, registry hives, drivers, and artifacts that do not exist on disk. Memory forensics is essential for investigating sophisticated attacks, fileless malware, rootkits, and live system activity.

This chapter explains what Volatility is, how it works, supported plugins, common workflows, and how investigators use it to extract actionable intelligence from memory images.

What Is Volatility?

Volatility is an open-source memory forensics tool designed to analyze RAM images captured using tools such as:

  • WinPmem

  • DumpIt

  • LiME

  • FTK Imager

  • Belkasoft RAM Capture

It supports multiple OSes and provides deep introspection into live memory structures. Volatility reconstructs kernel and user-space information without relying on the OS itself.

Volatility Versions

Volatility 2

  • Python 2-based

  • Stable and widely supported

  • Plugin-based architecture

  • Requires correct profile for analysis

Volatility 3

  • Python 3-based

  • Rewritten architecture

  • No profiles needed (auto-detects symbols)

  • Faster and more flexible

  • New plugin framework

Most investigators use both, depending on the case.

What Volatility Can Reveal

Volatility extracts a wide range of forensic data, including:

  • Running processes

  • Process trees

  • Injected code

  • DLL lists

  • Loaded kernel drivers

  • Network connections

  • ARP tables

  • Command history

  • Clipboard contents

  • Memory strings

  • Mutexes and handles

  • Registry keys

  • Malware implants

  • User activity artifacts

This makes RAM forensics critical for modern intrusion investigations.

Supported Operating Systems

Volatility supports:

Windows

  • XP → Windows 11

  • Extracts registry, processes, handles, drivers

Linux

  • Kernel-based introspection

  • Extracts processes, network, memory maps

macOS

  • Limited support depending on version

  • Extracts processes, modules, kernel tasks

Android

  • Parses Dalvik VM memory structures

  • Extracts running apps, caches, metadata

Volatility requires the correct symbol tables (especially on Linux/macOS).

Common Volatility Plugins (Most Used)

Process Analysis

pslist

Lists active processes.

pstree

Shows hierarchical process tree.

psscan

Recovers terminated or hidden processes (malware often hides).

DLL & Module Analysis

dlllist

Lists DLLs loaded by each process.

ldrmodules

Shows hidden or unlinked modules.

malfind

Detects injected code and suspicious memory regions.

Network Analysis

netscan

Reveals connections, ports, and sockets.

connscan

Finds terminated network connections.

sockscan

Extracts socket-level details.

Registry Analysis (Windows)

hivelist

Lists registry hives in memory.

printkey

Extracts registry values.

userassist, shimcache, amcache

User activity artifacts.

File System & Artefact Recovery

filescan

Finds file handles and paths in memory.

dumpfiles

Extracts files directly from RAM.

Memory Strings

strings

Extracts readable strings (IOC hunting).

Handle & Object Analysis

handles

Reveals handles to files, processes, registry keys.

mutantscan

Identifies mutex objects (useful for malware detection).

Malware Detection Plugins

malfind

Detects code injection, shellcode, and RWX regions.

yarascan

Scans memory with YARA rules.

apihooks

Finds hooked API functions (rootkits/malware).

Volatility 3 Plugins

Volatility 3 uses updated plugin names and architecture.

Common plugins:

  • windows.pslist

  • windows.psscan

  • windows.netscan

  • windows.dlllist

  • windows.malfind

  • windows.filescan

  • windows.vadinfo

  • windows.dumpfiles

The naming is modular and OS-specific.

Typical Volatility Workflow

1. Identify Memory Image Format

Example:

volatility -f memory.raw imageinfo

Identifies:

  • OS

  • Kernel version

  • Correct profile (Volatility 2)

2. Process Enumeration

volatility -f memory.raw --profile=Win10x64 pslist
volatility -f memory.raw pstree

Investigators look for:

  • Suspicious processes

  • Orphaned processes

  • Name-masked malware

3. Investigate Injected or Suspicious Processes

volatility malfind
volatility dlllist -p <PID>
volatility handles -p <PID>

Checks for:

  • Suspicious DLLs

  • RWX memory regions

  • Code injection

4. Analyze Network Connections

volatility netscan

Used to identify:

  • C2 traffic

  • Reverse shells

  • Persistent outbound connections

5. Extract Files & Binaries

volatility dumpfiles -Q <addr> -D output/

Useful for:

  • Dropped malware

  • Memory-resident payloads

6. Registry & User Activity Forensics

volatility hivelist
volatility printkey -K "Software\Microsoft\Windows\CurrentVersion\Run"

Reveals:

  • Persistence

  • Run keys

  • Malware configuration

7. Use YARA Rules to Detect Malware

volatility yarascan -y rules.yara

Matches malware signatures inside RAM.

Memory Image Acquisition Tools (Used with Volatility)

  • WinPmem

  • DumpIt

  • Belkasoft RAM Capture

  • FTK Imager

  • LiME (Android/Linux)

  • Magnet RAM Capture

Volatility requires a valid, complete memory dump.

Volatility in Malware Investigations

Memory forensics can uncover:

  • Fileless malware

  • In-memory RATs

  • PowerShell payloads

  • Cobalt Strike beacons

  • Reflective DLL injection

  • Rootkits

  • Kernel manipulation

Disk-based analysis cannot detect many of these artifacts.

When to Use Volatility

Volatility is ideal for:

  • Intrusion investigations

  • Ransomware root cause analysis

  • Fileless malware incidents

  • Live attack detection

  • Timeline reconstruction

  • Memory-only malware analysis

  • Incident response triage

Intel Dump

  • Volatility is a memory forensics framework for analyzing RAM dumps from Windows, Linux, macOS, and Android.

  • It identifies processes, injected code, DLLs, network connections, registry hives, handles, artifacts, and malware behavior.

  • Plugins like pslist, pstree, dlllist, netscan, malfind, filescan, and yarascan enable deep introspection.

  • Volatility 3 introduces a modern Python 3 architecture with OS-specific plugins and auto-detection of symbols.

  • Memory forensics is essential for detecting fileless malware, C2 beacons, in-memory payloads, and attacker activity invisible in disk forensics.

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