Skip to main content

A forensic tool for recovering deleted files from disk images.

Project description

Forensic Doctor 1.0.0

Forensic Doctor is a Python package designed for forensic analysis to recover deleted files from disk images, supporting a wide range of file types and sizes.

Installation

To install Forensic Doctor, use pip:

pip install forensic-doctor

Usage

Command Line

Recover and save to a specified path

forensic-doctor --recover--path /path/to/disk_image.E01 /path/to/folder/

Recover and save to a mentioned folder

forensic-doctor --recover--path /path/to/disk_image.E01 /path/to/folder/ --output /path/to/folder1/

Recover a mentioned file only

forensic-doctor --recover--file /path/to/disk_image.E01 /path/to/folder/image.png

Recover a mentioned file and move it to the specified path

forensic-doctor --recover--file /path/to/disk_image.E01 /path/to/folder/image.png --output /path/to/output_file/

Import as a Module

from forensic_doctor import recover_files, recover_file

# Example 1: Recover all files in a directory within the disk image
recovered_files = recover_files("/path/to/disk_image.E01", "/path/to/output_dir")
if recovered_files:
    for file in recovered_files:
        print(f"Recovered: {file}")
else:
    print("No files recovered.")

# Example 2: Recover a specific file from the disk image
recovered_file = recover_file("/path/to/disk_image.E01", "/path/to/image.png", "/path/to/output_file")
if recovered_file:
    print(f"Recovered: {recovered_file}")
else:
    print("File not recovered.")

# Example 3: Recover files and handle errors
try:
    recovered_files = recover_files("/path/to/disk_image.E01", "/path/to/output_dir")
    for file in recovered_files:
        print(f"Recovered: {file}")
except Exception as e:
    print(f"Error occurred: {e}")

# Example 4: Recover specific file and check file existence
recovered_file = recover_file("/path/to/disk_image.E01", "/path/to/image.png", "/path/to/output_file")
if recovered_file:
    print(f"Recovered: {recovered_file}")
    if os.path.exists(recovered_file):
        print("File exists.")
    else:
        print("File recovered but not found.")
else:
    print("File not recovered.")

# Example 5: Handle large files recovery
large_file_path = "/path/to/large_file.iso"
output_directory = "/path/to/output_dir"
recovered_files = recover_files(large_file_path, output_directory)
if recovered_files:
    print(f"Recovered {len(recovered_files)} files.")
else:
    print("No files recovered.")

Features

  • Supports recovery of all file types: images, videos, documents, etc.
  • Handles large and small files efficiently.
  • Command-line interface for quick and easy usage.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Thanks Note

Thank you for using Forensic Doctor! If you have any questions or need further assistance, feel free to reach out. Your feedback is valuable in improving this tool.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

forensic-doctor-1.0.0.tar.gz (4.4 kB view details)

Uploaded Source

Built Distribution

forensic_doctor-1.0.0-py3-none-any.whl (4.9 kB view details)

Uploaded Python 3

File details

Details for the file forensic-doctor-1.0.0.tar.gz.

File metadata

  • Download URL: forensic-doctor-1.0.0.tar.gz
  • Upload date:
  • Size: 4.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.11.2

File hashes

Hashes for forensic-doctor-1.0.0.tar.gz
Algorithm Hash digest
SHA256 e3ec83c1d884b837fdb12fe9f6f9bfb80c844e08c7337395ae06234305f5412a
MD5 cfe483df6b0a6b687af0c8a1cada39eb
BLAKE2b-256 7eab7c0be1a501ebde128bf91b732c392c1229b5b8ee64fbe8a9a205a29ca5da

See more details on using hashes here.

File details

Details for the file forensic_doctor-1.0.0-py3-none-any.whl.

File metadata

File hashes

Hashes for forensic_doctor-1.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 381ab979d981183a92b8ed2002979725c26887be08068da03599cf73ca353001
MD5 d740898121f5ff0a15ed901322547bb6
BLAKE2b-256 d5546e0fd4c753ae5445353adae12194dc4086c261b149e13b2e5cbbe340eb46

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page