Password Strength Analysis and Recommendation System Using Django

- In today's digital landscape, weak passwords remain a significant security vulnerability, contributing to numerous data breaches and unauthorized access attempts. This research presents a Password Strength Analysis and Recommendation System developed using Django framework. The system addresses the critical need for better password security by providing users with comprehensive tools to generate strong passwords and analyze password strength in real-time. The implementation uses regex and random libraries for password generation based on user-provided information, while the zxcvbn library provides sophisticated password strength evaluation. Visual representation through bar plots helps users understand password composition across four key elements: lowercase letters, uppercase letters, numbers, and special characters. User testing demonstrates improved awareness of password security practices and creation of stronger passwords. The system's integration of visual feedback and real-time analysis represents a significant improvement over existing password management tools, contributing to enhanced cybersecurity practices. Key Words: Password Strength, Django Framework, Password Generation, Password Analysis, Cybersecurity, User Authentication, zxcvbn, Regex, Random, Bar Plots.

Authors

Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-03-05
DOI
https://doi.org/10.55041/ijsrem42111
Primary Topic
User Authentication and Security Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Password Strength Analysis and Recommendation System Using Django

Boyina Manikanta
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
User Authentication and Security Systems
article

Password Strength Analysis and Recommendation System Using Django

Boyina Manikanta
article en

Abstract

- In today's digital landscape, weak passwords remain a significant security vulnerability, contributing to numerous data breaches and unauthorized access attempts. This research presents a Password Strength Analysis and Recommendation System developed using Django framework. The system addresses the critical need for better password security by providing users with comprehensive tools to generate strong passwords and analyze password strength in real-time. The implementation uses regex and random libraries for password generation based on user-provided information, while the zxcvbn library provides sophisticated password strength evaluation. Visual representation through bar plots helps users understand password composition across four key elements: lowercase letters, uppercase letters, numbers, and special characters. User testing demonstrates improved awareness of password security practices and creation of stronger passwords. The system's integration of visual feedback and real-time analysis represents a significant improvement over existing password management tools, contributing to enhanced cybersecurity practices. Key Words: Password Strength, Django Framework, Password Generation, Password Analysis, Cybersecurity, User Authentication, zxcvbn, Regex, Random, Bar Plots.

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(03)
Peace, Justice and strong institutions
Openalex Percentile: Top 95%
User Authentication and Security Systems
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