🔐 Advanced Password Strength Analyzer

An AI-powered, multi-layered password evaluation and generation system designed to identify vulnerabilities, improve password robustness, and assist users in creating secure yet memorable passwords. It integrates traditional security techniques, statistical analysis, and Generative AI for end-to-end password security enhancement.

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🎯 Objective

The goal of this system is to analyze the strength of a password through multi-dimensional evaluation layers and provide intelligent suggestions to improve password security. By simulating different types of real-world attacks (e.g., brute force, social engineering, breached databases), it ensures each password undergoes rigorous scrutiny.

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🧠 Technology Stack

• Frontend: React.js
• Backend: Flask
• Authentication: JWT (JSON Web Tokens)
• Password Hashing & Security: bcrypt, Bloom filters
• Security Models & Logic: zxcvbn, Entropy calculations
• Explainability: SHAP (SHapley Additive exPlanations)
• Generative AI: Mistral LLM for intelligent feedback and password generation
• Data: Breached datasets like RockYou, LinkedIn leaks

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🔐 Multi-Layered Architecture

This system evaluates passwords across five key layers, each simulating a real-world attack vector or analysis dimension:

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1️⃣ Breached Password Identification

• Type: Brute Force Attack Simulation
• Approach: Checks the password against known leaked datasets like RockYou and LinkedIn dumps using Bloom Filters for fast lookup.
• Goal: Prevent the use of passwords that are already publicly exposed.

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2️⃣ Banned & Fuzzy Word Detection (PII-Based)

• Type: Social Engineering Attack Simulation
• Approach: Identifies passwords containing or resembling personal identifiable data (PII) such as names, DOBs, email fragments using fuzzy matching.
• Goal: Detect predictable or easily guessable patterns related to user identity.

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3️⃣ Password Composition Strength Analysis

• Type: Pure Brute Force Simulation
• Approach: Analyzes structure based on character types (uppercase, lowercase, digits, symbols), repetition patterns, keyboard adjacency, and dictionary patterns using zxcvbn.
• Goal: Evaluate complexity against generic brute-force attacks.

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4️⃣ Entropy Calculation & Crack Time Estimation

• Approach: Calculates Shannon entropy and uses combinatorial logic to estimate crack time against common attack strategies.
• Goal: Quantify randomness and evaluate resilience to password cracking tools.

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5️⃣ GenAI-Based Password Strength Feedback and Generation

• Approach:
  • Uses Mistral LLM to generate strong passwords tailored to security requirements.
  • Interactively updates password based on user queries (e.g., "make it easier to remember", "add a special character", "use a word I like").
• Goal: Achieve a balance between security, unpredictability, and user memorability.

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💬 AI-Powered Feedback Loop

Each layer provides:

• Scoring
• Risk Explanation using SHAP
• Actionable Suggestions from LLM

The system returns an aggregated strength score, visual feedback, and intelligent suggestions that adapt based on specific vulnerabilities detected in each layer.

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🔄 Password Generation System

• Users can query the LLM to generate passwords that:
  • Avoid banned patterns
  • Match complexity standards
  • Are easier to remember while maintaining entropy
• Includes interactive update system that lets users modify generated passwords (e.g., change structure, add memorable phrases).

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🧪 Features Overview

Feature	Description
Password Strength Analysis	Layered evaluation using breached data, PII check, zxcvbn, entropy, and LLM
Leak Detection	Breach dataset lookup with Bloom filters
Pattern Analysis	Detects predictable or weak sequences
Entropy Check	Measures cryptographic randomness
SHAP Explainability	Interprets feature impact for each password
Dictionary Matching	Compares with common words and passwords
PII Detection	Detects use of name, email, DOB patterns
Strong Password Generator	GenAI-driven custom password creation
Crack Time Estimation	Estimates how long a password would take to crack
Bulk Password Validation	For enterprise-wide audits
Password Expiration Alerts	Notifies users of outdated passwords
Password History Check	Prevents reuse of recent passwords
Admin Control Panel	Configure organizational security policies
Enterprise Password Uniqueness	Ensures password uniqueness across teams
AI Feedback	Explains weaknesses and gives personalized suggestions

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🧰 Skills & Technologies Used

• Artificial Intelligence (AI)
• Machine Learning
• Bloom Filters
• zxcvbn Password Analysis
• Large Language Models (LLM) – Mistral
• SHAP (Explainability)
• bcrypt for Hashing
• JWT (JSON Web Tokens)
• React.js (Frontend)
• Flask (Backend)

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📌 Use Cases

• Developers: Integrate into login systems or password checkers.
• Enterprises: Conduct audits, enforce password policies, and detect weak credentials.
• Users: Get real-time feedback and generate secure, personalized passwords.
• Security Auditors: Perform breach checks and pattern evaluations at scale.

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