LSTM Vulnerability Fix Generation with Pre-Deployment Validation

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Solution Overview

Problem

Managers face difficulties in accurately, efficiently, and automatically implementing vulnerability fixes in computing environments, particularly when new vulnerabilities arise, to ensure continued functionality without hindering the computing environment's purpose.

Innovation Solution

A system utilizing a long short-term memory network model to generate potential fixes, assess their functionality and vulnerability confidence metrics, and implement them only when both metrics meet predefined thresholds, with an option to generate updated fixes if initial ones are not suitable.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual vulnerability fix implementation is used, then managers can control and review each fix, but the process is time-consuming and prone to human error

Engineering Contradiction:

Improveaccuracy of vulnerability fix implementationVSAvoidtime to implement vulnerability fixes

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system enables automated self-service vulnerability fix implementation through AI-generated code patches that are automatically tested, validated, and deployed without manual intervention. The system autonomously monitors vulnerabilities, generates fixes, and implements them across the computing environment, eliminating the need for manual review and implementation while maintaining high accuracy through multiple validation checks.

Inventive Principle:

Principle #25Self-service

2Productivity

If automated vulnerability fix systems are implemented, then processing speed increases, but the complexity of the system increases

Engineering Contradiction:

Improvespeed of vulnerability fix implementationVSAvoidsystem complexity for vulnerability management

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The vulnerability management system performs multiple functions through a unified AI-powered platform: vulnerability detection, fix generation, code testing, validation, and deployment. This multi-functional approach consolidates what would otherwise require separate complex systems into a single integrated solution, managing complexity while maintaining high productivity through automated operations.

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Reliability

If vulnerability fixes are implemented quickly, then security posture improves, but the risk of introducing functional errors increases

Engineering Contradiction:

Improvesecurity reliability of computing environmentVSAvoidfunctional errors from rapid fix implementation

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The system performs preliminary testing and validation of vulnerability fixes in isolated test environments before deploying them to production. AI-generated fixes are first subjected to automated code analysis, unit testing, and integration testing to verify they resolve the vulnerability without introducing functional errors. Only after successful validation are fixes implemented in the live computing environment, ensuring security improvements without compromising functionality.

Inventive Principle:

Principle #10Preliminary action

4Measurement precision

If comprehensive vulnerability assessment is performed, then fix accuracy improves, but computational resources are consumed

Engineering Contradiction:

Improveaccuracy of vulnerability assessmentVSAvoidcomputing resources for vulnerability analysis

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The system applies targeted vulnerability assessment strategies that focus computational resources on the most critical vulnerabilities and high-risk computing environment components. AI algorithms prioritize assessment based on vulnerability severity, exploitability, and impact potential, performing comprehensive analysis only where necessary while using streamlined assessment methods for lower-risk items, thereby balancing accuracy with resource efficiency.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS12411959B2Systems, methods, and apparatuses for detecting and implementing vulnerability fixes in an electronic environment

Publication Date: 2025.09.09 BANK OF AMERICA CORP

AI summary

Systems, computer program products, and methods are described herein for detecting and implementing vulnerability fixes in an electronic environment. The present disclosure is configured to: receive a vulnerability trigger; parse data associated with the vulnerability trigger; generate a vulnerability assessment environment and apply the parsed data; generate vulnerability assessment data comprising at least one computing environment component associated with the vulnerability trigger; apply a long short-term memory network model to the vulnerability assessment data to generate at least one potential fix for the at least one computing environment component; input the at least one potential fix to at least one potential fix assessment environment; generate a functionality confidence metric and a vulnerability confidence metric for the at least one potential fix associated with the at least one computing environment component; and implement the at least one potential fix for the at least one computing environment component.