AI Vulnerability Mitigation for Faster Enterprise Remediation

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Solution Overview

Problem

Existing methods for identifying and mitigating vulnerabilities in enterprise systems are inefficient, requiring human intervention and leading to delays in remediation, which can result in security breaches and loss of resources.

Innovation Solution

A system utilizing artificial intelligence and machine learning to automatically detect and mitigate vulnerabilities by comparing software configuration data against a database of known vulnerabilities, using neural networks to classify vulnerabilities and execute remediation protocols.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of time

If traditional manual methods are used to identify and mitigate vulnerabilities, then human agents can classify and remediate vulnerabilities, but the time required for vulnerability remediation increases and security exposure is extended

Engineering Contradiction:

Improvetime between vulnerability identification and remediationVSAvoidautomation of vulnerability detection and remediation

Core Design Contradiction:

Loss of timeVSExtent of automation

Solution Approach 1:

The vulnerability mitigation system performs self-service by automatically detecting, classifying, and remediating vulnerabilities without requiring human intervention. The system captures system data, compares it against vulnerability databases, executes classification algorithms to determine vulnerability types, and automatically applies remediation measures, enabling the system to service itself throughout the entire vulnerability management lifecycle.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system performs preliminary action by continuously capturing and analyzing system data in real-time, maintaining an updated vulnerability database, and pre-configuring remediation protocols before vulnerabilities are exploited. The system proactively identifies vulnerabilities by comparing current system state against known vulnerability patterns, enabling remediation to occur before attacks can succeed.

Inventive Principle:

Principle #10Preliminary action

2Reliability

If manual vulnerability management processes are used, then human agents can address vulnerabilities, but the severity and impact of vulnerabilities increase due to delays in remediation

Engineering Contradiction:

Improvesecurity reliability and vulnerability mitigation effectivenessVSAvoidcomplexity of automated vulnerability management system

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The vulnerability management system is segmented into distinct functional modules: a data capture module that collects system information, a comparison module that matches systems against vulnerability databases, a classification module that algorithmsically determines vulnerability types, and a remediation module that applies fixes. This segmentation allows each component to specialize in its function, improving overall reliability while managing complexity through modular design.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system employs an intermediary vulnerability database that acts as a mediator between system data and remediation actions. The database stores known vulnerability patterns, classification rules, and remediation protocols, serving as an intermediate knowledge base that enables automated decision-making without requiring complex hard-coded logic throughout the system.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Productivity

If automated systems are implemented to detect and remediate vulnerabilities, then remediation time is reduced and security is enhanced, but the system complexity increases

Engineering Contradiction:

Improvevulnerability remediation speed and efficiencyVSAvoidcomplexity of automated classification and remediation system

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The automated system is designed with multi-functionality to handle diverse vulnerability types through a unified platform. The classification algorithm can identify multiple vulnerability categories (software vulnerabilities, configuration errors, missing patches), and the remediation module can apply various fix types (patches, configuration changes, alerts) through a single system interface, improving productivity without proportionally increasing complexity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20260032143A1Systems and methods for automatic vulnerability mitigation

Publication Date: 2026.01.29 TRUIST BANK

AI summary

Disclosed are systems and methods for detecting a vulnerability across programs of an enterprise system and automatically mitigating the vulnerability. The systems and methods utilize artificial intelligence (“AI”) systems to process data received from a particular network, such as systems data, software data, and software configuration data. The AI systems processes the software data and software configuration data and compares the data to known vulnerabilities stored to a database. The system maps the vulnerabilities to attack signatures. When a vulnerability is identified within the network, the AI systems run classification analysis and categorization analysis to determine the probability a vulnerability is a known vulnerability and the category of software it relates to. The system self-executes a rule that enables the attack signatures to protect against the identified vulnerability by either removing or patching.