Inadvertent Password Entry Detection System
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Solution Overview
Problem
Existing user interfaces fail to effectively prevent inadvertent entry of passwords into non-password entry fields, leading to potential security vulnerabilities such as unencrypted logging and insecure transmission of sensitive information.
Innovation Solution
A method and system that monitor text or data entered into non-password entry fields to determine if it is likely a password, using techniques like password complexity checks, password manager integration, hash value comparison, and Bloom filters, and take actions such as warning, removal, or obscuration to prevent inadvertent password entry.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If password entry fields are provided in user interfaces, then secure access control is enabled, but users may inadvertently enter passwords into non-password fields leading to security vulnerabilities
Solution Approach 1:
The system performs preliminary detection by monitoring text entry fields before password submission occurs. It proactively identifies potential password entries in non-password fields by comparing entered text against stored password hashes, and prevents inadvertent exposure by blocking submission or alerting the user before the security breach can occur.
Solution Approach 2:
The patent introduces an intermediary monitoring layer between the user interface and the authentication system. This intermediary component intercepts text inputs, analyzes them against password criteria, and mediates whether the input should be processed as a password or rejected, thereby protecting the system without modifying the underlying authentication mechanism.
2Object-affected harmful factors
If all text fields are monitored for password entry, then inadvertent password exposure is prevented, but system complexity and processing overhead increase
Solution Approach 1:
The monitoring system applies different levels of scrutiny to different fields based on their security sensitivity. Password fields are monitored with full hash comparison, while other text fields receive lighter monitoring that checks only for password-like patterns. This localized approach maintains high security where needed while reducing complexity in less critical areas.
Solution Approach 2:
The system dynamically adjusts monitoring parameters based on field context. It changes the detection sensitivity, comparison methods, and alert thresholds depending on whether the field is a password field, search field, or other text input. This parameter adaptation allows the system to maintain effectiveness across diverse fields while optimizing performance and reducing unnecessary processing.
Data Source
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AI summary
Systems and methods for monitoring data input are disclosed. A dataset entered into a non-password field is received. Based on the dataset meeting one or more criteria for a likely password, a determination as to whether the dataset is inadvertently entered into the non-password field is made. Based on determining that the dataset is inadvertently entered into the non-password field, further processing of the dataset is inhibited.