Automated Vulnerability Identification System

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Enterprises face challenges in efficiently identifying and tracking application vulnerabilities across their critical business infrastructure, particularly due to reliance on third-party developed applications and frequent updates, which can lead to resource-intensive monitoring and vulnerability reporting processes.

Innovation Solution

A system and method for identifying and tracking application vulnerabilities, involving a program assessment module to analyze source code for vulnerabilities, a vulnerability optimization module to tag and synchronize data, and a reporting database to generate analytics and reports, facilitating efficient tracking and remediation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If enterprises monitor applications and track vulnerabilities manually, then vulnerability identification can be performed, but resource consumption increases significantly

Engineering Contradiction:

Improvevulnerability identificationVSAvoidresource consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The patent replaces manual vulnerability monitoring processes with an automated system that uses machine learning models to predict and identify vulnerabilities. The system automatically scans source code, predicts vulnerability locations, and tracks remediation progress without requiring manual intervention, thereby reducing resource consumption while maintaining identification reliability.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The vulnerability tracking system performs self-service by automatically generating vulnerability reports, updating risk predictions, and monitoring remediation status without requiring continuous human oversight. The system self-updates its knowledge base with new vulnerability patterns and automatically adjusts its scanning priorities based on predicted risk levels.

Inventive Principle:

Principle #25Self-service

2Measurement precision

If enterprises conduct comprehensive vulnerability scanning, then vulnerability detection improves, but processing time and requirements increase

Engineering Contradiction:

Improvevulnerability detectionVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs preliminary actions by pre-training machine learning models on historical vulnerability data and pre-configuring scanning parameters based on predicted risk patterns. Before actual vulnerability scanning occurs, the system prepares risk prioritization rules and scanning heuristics, enabling faster execution during actual vulnerability detection without compromising precision.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent applies local quality by focusing scanning resources on specific high-risk areas identified by machine learning predictions rather than uniformly scanning entire codebases. The system dynamically adjusts scanning intensity and coverage based on predicted vulnerability probabilities, applying more thorough analysis to high-risk sections while using lighter scanning methods for low-risk areas.

Inventive Principle:

Principle #3Local quality

3Measurement precision

If enterprises track all vulnerability details, then vulnerability tracking accuracy improves, but data management complexity increases

Engineering Contradiction:

Improvevulnerability tracking accuracyVSAvoiddata management complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system extracts and stores only the most critical vulnerability information needed for tracking and risk assessment, such as vulnerability ID, location, predicted risk level, and remediation status. Less detailed information about vulnerability patterns and scanning metadata is processed temporarily but not stored long-term, reducing data management complexity while maintaining tracking accuracy for essential vulnerability attributes.

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS9507946B2Program vulnerability identification

Publication Date: 2016.11.29 BANK OF AMERICA CORP

AI summary

In one embodiment, a system for identifying and tracking application vulnerabilities includes an interface, a processor, and a memory. The interface is operable to receive a plurality of applications from one or more business units, each of the plurality of applications including source code. A process is communicatively coupled to the interface and is operable to identify a vulnerability associated with the source code of each of the plurality of applications. A memory is communicatively coupled to the interface and the processor and operable to store the vulnerability and the source code associated with the vulnerability in a vulnerability database. The processor is further operable to create a vulnerability tag for the vulnerability stored in the vulnerability database. The memory may also store the vulnerability tag for the vulnerability in a reporting database.