allykit 1.0.5

A comprehensive Python toolkit for security engineering, cryptography, web scraping, filesystem auditing, DFIR, and reusable utility functions.

allykit Library Documentation

The allykit library is a comprehensive toolkit designed for security engineers, backend developers, and digital forensics specialists. It integrates advanced cryptographic operations, automated web interaction, intelligent filesystem auditing, and robust password management into a unified framework.

Modules Overview

1. Password Generation & Security kit

A high-level suite for managing credentials. It supports the generation of complex, randomized strings and time-sensitive passwords with expiration logic.

• Core Capabilities: Customizable password generation (length, character constraints, prefixes/suffixes), time-based validity (GTP/WPWT), and granular security auditing (Complexity Scoring and validation engines).
• Use Cases: Automated credential management, secure token generation, and security strength evaluation.

2. Web kit & Scrapers

A specialized module for seamless web interaction and data extraction.

• Core Capabilities: Advanced HTML fetching (mimicking real browsers to bypass detection), DOM traversal via BeautifulSoup integration, and memory-efficient streaming for large remote file downloads.
• Use Cases: Web scraping, data mining, and automated media/asset acquisition.

3. Cryptographic Hashing & Integrity Verification

A robust cryptographic engine providing multi-algorithm support and advanced protection mechanisms.

• Core Capabilities: Support for the SHA family (SHA-1 through SHAKE-256), intelligent hash detection, Salt management to prevent rainbow table attacks, and "Hash-in-Hash" (HH) double-hashing for increased computational difficulty.
• Use Cases: Digital forensics, data integrity verification, and secure authentication layers.

4. Filesystem Management & Metadata Mapping

An advanced exploration engine for deep filesystem analysis and auditing.

• Core Capabilities: Recursive directory crawling, hierarchical metadata mapping (size, ownership, timestamps), and structured filesystem inventory generation.
• Use Cases: Digital forensics (DFIR), system auditing, and integrity-based backup solutions.

5. Global Constants & Data Definitions

A centralized repository for standardized datasets used across all modules.

• Core Capabilities: Internationalization (country codes), Localization (Persian alphabet and Iranian geography), Character Set classifications (ctype-style), and System Security constants (octal permission masks).
• Use Cases: Providing a single source of truth for validation, translation, and security permission checks.

Technical Requirements

• Environment: Python 3.x
• Dependencies: pip install selenium beautifulsoup4 requests tenacity deepdiff
• Standard Libraries: hashlib, os, pathlib, datetime, json, shutil, string, random, re, typing