The Volatility Framework is a completely open collection of tools, implemented in Python, for the extraction of digital artifacts from volatile memory (RAM) samples.
The extraction techniques are performed completely independent of the system being investigated but offer visibility into the runtime state of the system. The framework is intended to introduce people to the techniques and complexities associated with extracting digital artifacts from volatile memory samples and provide a platform for further work into this exciting area of research.
Volatility was designed by forensics, incident response, and malware experts to focus on the types of tasks these analysts typically form.
Features include:
- Single, cohesive framework analyzes RAM dumps from 32- and 64-bit windows, linux, mac, and android systems. Volatility’s modular design allows it to easily support new operating systems and architectures as they are released.
- Carving.
- Command histories.
- Console input/output buffers.
- USER objects (GUI memory).
- Network related data structures.
- Extensible and scriptable API.
- Fast and efficient algorithms let you analyze RAM dumps from large systems without unnecessary overhead or memory consumption.
- Supports a variety of sample file formats and the ability to convert between these formats:
- Raw linear sample (dd).
- Hibernation file (from Windows 7 and earlier).
- Crash dump file.
- VirtualBox ELF64 core dump.
- VMware saved state and snapshot files.
- EWF format (E01).
- LiME format.
- Mach-O file format.
- QEMU virtual machine dumps.
- Firewire HPAK (FDPro).
- Cross-platform support – runs under Linux, Mac OS X, and Windows.
Website: www.volatilityfoundation.org
Support: Documentation Project, GitHub Code Repository
Developer: Brder
License: GNU General Public License v2.0
Volatility is written in Python. Learn Python with our recommended free books and free tutorials.
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