volatility

volatility [GLOBAL_OPTIONS] -f [--profile=] [PLUGIN_OPTIONS]

-f FILE, --file FILE
    Specifies the path to the memory dump file to be analyzed.

--profile=PROFILE
    (Volatility 2) Specifies the KDBG profile that matches the operating system, service pack, and architecture of the memory dump. This is crucial for accurate analysis.

--plugins=DIRECTORY
    Adds a directory to the plugin search path, allowing custom or additional plugins to be loaded.

--output=FORMAT
    Determines the output format of the plugin results (e.g., text, json, csv).

--output-file=FILE
    Writes the plugin output to the specified file instead of standard output.

--verbose
    Enables verbose output, providing more detailed information during execution.

--debug
    Activates debugging mode, useful for troubleshooting issues or understanding internal operations.

-h, --help
    Displays the global help message or specific help for a given plugin.

--info
    Displays information about available plugins, profiles, and configurations.

Volatility is a powerful, open-source memory forensics framework written in Python. It's designed for extracting digital artifacts from volatile memory (RAM) dumps, enabling incident responders and forensic analysts to analyze the runtime state of a system. Unlike disk-based forensics, memory forensics allows for the discovery of volatile data that might not be written to disk or could be easily manipulated.

It supports a wide range of operating systems including Windows, Linux, and macOS, providing a unified platform for memory analysis across different environments. Volatility can reveal crucial information such as running processes, open network connections, loaded kernel modules, hidden processes, injected code, registry keys, command history, and much more, making it an indispensable tool for identifying malicious activity, understanding attack methodologies, and gathering evidence during a security incident.

• Installation Required: Volatility is not a standard Linux command and must be installed separately, typically via Python's package manager (pip) or by cloning its GitHub repository.
• Memory Dumps Only: Volatility analyzes existing memory dumps; it does not acquire them. Separate tools like LiME (Linux), WinPMEM (Windows), or F-Response are used for memory acquisition.
• Profile Dependency (Volatility 2): For Volatility 2, selecting the correct OS profile matching the memory dump is critical. An incorrect profile will lead to erroneous or no results. Volatility 3 has improved profile auto-detection.
• Steep Learning Curve: Due to its extensive number of plugins and the complex nature of memory forensics, understanding and effectively using Volatility can have a steep learning curve.
• Legal & Ethical Considerations: Acquiring and analyzing memory dumps involves sensitive data and raises significant legal and ethical considerations regarding privacy and data handling.

The power of Volatility lies in its modular plugin system. Each plugin is designed to perform a specific forensic task, such as listing processes (pslist), enumerating network connections (netscan), extracting command history (cmdscan), or finding hidden rootkits. Users select a plugin based on the information they wish to extract from the memory dump.

There are two major versions in active use: Volatility 2 and Volatility 3. Volatility 3 (often invoked as vol.py) is a complete rewrite, offering a more unified codebase for different operating systems and an improved plugin architecture. While Volatility 2 still sees use, particularly for older profiles or specific plugins, Volatility 3 is the actively developed and recommended version for new work due to its enhancements and future-proofing.

Volatility originated as a research project at BlackHat USA 2007 by Aaron Walters. It quickly evolved into an open-source project, becoming the de-facto standard framework for memory forensics. The Volatility Foundation was established to support its continued development and community. The project saw a major architectural rewrite with the release of Volatility 3 (vol.py), aiming for improved performance, extensibility, and a unified API across different operating systems, moving away from the need for explicit profiles for every dump. This rewrite addressed many limitations of Volatility 2 while maintaining its core functionality.

strings(1), dd(1), lsof(8), netstat(8), ps(1), gdb(1), foremost(1)