LLM Remediation Descriptions for Outdated Vulnerability Records

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Solution Overview

Problem

Cybersecurity systems lack interpretable and accurate recommendations for remediation actions for newly detected or outdated vulnerabilities, posing a logistical challenge in cataloging patch fixes for software and firmware configurations.

Innovation Solution

A pipeline utilizing a large language model (LLM) to generate formatted descriptions of remediation actions by crawling web pages associated with vulnerabilities, parsing content, and generating prompts to produce structured remediation recommendations, followed by a cleaning module to ensure accuracy and consistency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual inspection of online vulnerability descriptions is used to generate remediation recommendations, then accuracy and interpretability of recommendations are improved, but productivity and scalability deteriorate

Engineering Contradiction:

Improveaccuracy of remediation recommendationsVSAvoidspeed of generating remediation descriptions

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The patent introduces a large language model as an intermediary between raw vulnerability data and remediation recommendations. The LLM processes crawled vulnerability information and generates accurate, interpretable remediation descriptions without requiring manual inspection, thus maintaining reliability while improving productivity

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system enables automated self-service generation of remediation recommendations by having the LLM process vulnerability data independently. The pipeline automatically crawls, parses, and generates recommendations without human intervention, eliminating the productivity bottleneck of manual inspection while maintaining accuracy through the LLM's capability

Inventive Principle:

Principle #25Self-service

2Loss of information

If comprehensive web crawling is performed to gather vulnerability information, then completeness and accuracy of remediation descriptions are improved, but loss of time and computational resources worsens

Engineering Contradiction:

Improvecompleteness of vulnerability dataVSAvoidtime for crawling and processing

Core Design Contradiction:

Loss of informationVSLoss of time

Solution Approach 1:

The system performs preliminary web crawling to gather comprehensive vulnerability information before the LLM generation step. By collecting all necessary data upfront from multiple sources (NVD, vendor websites, security advisories), the pipeline ensures complete information is available for accurate recommendation generation without repeated crawling

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent divides the information gathering process into segmented steps: crawling specific vulnerability databases, parsing individual web pages, extracting relevant fields, and feeding structured data to the LLM. This segmentation allows efficient processing of comprehensive data without overwhelming computational overhead at any single stage

Inventive Principle:

Principle #1Segmentation

3Ease of operation

If formatted descriptions are generated for all vulnerabilities, then usability and integrity of vulnerability documentation are improved, but device complexity and processing overhead worsens

Engineering Contradiction:

Improveusability of vulnerability documentationVSAvoidcomplexity of processing pipeline

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The patent transforms unstructured vulnerability data into structured formatted descriptions with specific parameters (affected configurations, remediation actions, version information). This parameterization improves usability by making documentation consistent and machine-readable while the modular pipeline manages complexity through standardized processing steps

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20260037635A1Large language model-based vulnerability remediation action descriptions

Publication Date: 2026.02.05 PALO ALTO NETWORKS INC

AI summary

A vulnerability documentation system detects vulnerabilities having outdated or undocumented formatted descriptions for corresponding remediation actions. A web crawler crawls the Internet for configuration data for software/firmware affected by the detected vulnerabilities and descriptive content for the remediation actions. The vulnerability documentation system prompts and LLM with a prompt for each detected vulnerability comprising instructions to generate a formatted description for remediation actions using the crawled configuration data/descriptive content. The vulnerability documentation system then populates natural language descriptions of remediation actions from the formatted descriptions and pushes the natural language descriptions to affected devices.