Forensics Use Cases

File Metadata Extraction

Extracting metadata from various file types (e.g., timestamps, authors, and geolocation data from images).

Libraries to consider os, PIL (for images), pyPDF2 (for PDFs).

File Integrity Checks

Computing cryptographic hashes (e.g., MD5, SHA-256) to verify file integrity and detect alterations.

Libraries to consider hashlib.

File Signature Analysis

Identifying file types based on their headers (magic numbers) to detect disguised malicious files.

Libraries to consider python-magic.

File Recovery

Recovering deleted files from disk images or storage devices.

Libraries to consider pytsk (Python binding for The Sleuth Kit).

Log File Analysis

Parsing and analyzing log files for signs of malicious activity.

Libraries to consider re (regular expressions), built-in file handling functions.

File Carving

Extracting known file types from raw data, useful for recovering files from unallocated disk space.

Libraries to consider foremost, scalpel (though not Python libraries, they can be invoked using Python's subprocess module).

File System Analysis

Analyzing file system structures, extracting artifacts, and identifying suspicious activities.

Libraries to consider pytsk, dfvfs.

Steganography Detection

Detecting hidden data within files, especially images and audio files.

Libraries to consider stegano, stepic.

File Activity Timeline

Creating a timeline of file activities (e.g., creation, modification, access) to track user or malware actions over time.

Libraries to consider os, pytsk.

Automated File Scanning

Scanning files using multiple antivirus engines or threat intelligence platforms.

Libraries to consider VirusTotal API, opswat-metadefender-cloud-sdk.

Binary File Analysis

Analyzing binary files to extract strings, headers, or other relevant data.

Libraries to consider pyelftools (for ELF binaries), pefile (for PE binaries).

File Content Search

Searching for specific patterns, keywords, or sensitive information within files.

Libraries to consider re (regular expressions).

File Compression and Archive Analysis

Analyzing compressed files and archives to extract and investigate their contents.

Libraries to consider zipfile, tarfile.

Automated File Classification

Classifying files based on their content, type, or other attributes to quickly identify potential threats.

Libraries to consider scikit-learn, tensorflow (for machine learning-based classification).