volatility3
Memory forensics framework
What it is and what it does
Volatility 3 is a complete rewrite of the original Volatility framework, designed to extract and analyze digital artifacts directly from volatile memory (RAM) samples. It operates independently of the target system's operating system, providing visibility into the runtime state without requiring the system to be running. The framework supports Windows, Linux, and macOS memory analysis through a plugin architecture accessible via the command-line `vol` tool.
The package requires Python 3.8.0 or later and depends only on pefile for its core functionality. Symbol tables—which map memory addresses to kernel symbols—must be obtained separately for each supported OS and placed in the symbols directory. Windows symbols can be automatically queried and cached, but macOS and Linux symbols require manual generation using tools like dwarf2json. The framework is intended both for forensic investigation and as a platform for research into memory artifact extraction techniques.
Use it for:
- Analyze Windows memory dumps to identify running processes, network connections, and malware artifacts in incident response.
- Extract kernel data structures and runtime state from Linux memory samples for post-mortem system analysis.
- Investigate macOS memory dumps to recover deleted files, encryption keys, and user activity traces.
- Develop custom plugins to extract domain-specific artifacts from memory for specialized forensic workflows.
- Research memory forensics techniques and validate new artifact extraction methods against real memory samples.
Worth the install?
AI-flagged interpretation of the facts on this page — verify before relying
Volatility 3 is a memory forensics framework that extracts and analyzes digital artifacts from volatile RAM samples across Windows, Linux, and macOS systems.
Yes, if you work in digital forensics or incident response. Volatility 3 is the industry-standard memory analysis framework with active maintenance, low install friction, and no known vulnerabilities. The custom VSL license requires review for your use case, but the framework itself is stable and widely adopted. Install it if you need to analyze memory dumps; skip it if you have no forensic analysis requirements.
Install
volatility3 on PyPI
pip
pip install volatility3uv
uv add volatility3poetry
poetry add volatility3Installing volatility3
Before you install
Low install friction with a single runtime dependency (pefile). The project is actively maintained with recent commits and a stable release cycle; last commit was 2026-08-14 and the latest release is 2026-04-30.
License in practice
Licensed under the Volatility Software License (VSL), which is a custom license distinct from common open-source licenses. The license treatment is marked unclear, so you should review the full VSL v1.0 at https://www.volatilityfoundation.org/license/vsl-v1.0 before using in commercial or redistributed contexts.
Quickstart
pip install volatility3
from volatility3.cli import main
# Run a plugin on a memory sample
vol -f /path/to/memory.vmem windows.info
Requires Python 3.8.0 or later. Symbol table packs for Windows, macOS, and Linux must be downloaded separately and placed in the volatility3/symbols directory; first run with new symbol files requires cache initialization which may take time.
Verify before relying
- Whether the VSL license permits commercial use or redistribution without additional restrictions beyond what is stated in the license text.
- Performance characteristics and memory overhead when analyzing large memory samples.
- Compatibility with memory dumps from systems other than Windows, macOS, and Linux.
Package facts
| License | VSL (unclear) |
| Python support | supports the current Python release (>=3.8.0) |
| Install friction | low — pure-Python wheel |
| Runtime dependencies | 1 — pefile |
| Maintenance | actively maintained — 106 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 74,631/month — #14,809 on PyPI (30-day window, as of 2026-08-14) |
| Known vulnerabilities | none known (OSV.dev, checked 2026-08-14) |
Evidence: volatility3-2.28.0-py3-none-any.whl
Keywords: volatility, memory, forensics, framework, windows, linux, volshell
Tags
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