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CVSS (Common Vulnerability Scoring System)
Open source industry standard for assessing the severity of computer vulnerabilities by generating a numerical score based on exploitability, impact, and temporal metrics.
Contextual criticality scoring
Adaptive evaluation methodology that weights vulnerability severity according to company-specific factors, including asset criticality, network exposure, and business context.
Exploitation prediction model
Machine learning algorithm trained on historical incident data to estimate the probability that a vulnerability will be actively exploited in a given environment.
Predictive artificial intelligence in cybersecurity
Set of ML and deep learning techniques applied to threat anticipation by analyzing complex patterns to predict critical vulnerabilities before their exploitation.
Dynamic risk assessment
Continuous process of analyzing and updating the risk level associated with vulnerabilities based on context evolution, emerging threats, and infrastructure changes.
Threat contextualization
Integration of multiple data sources (threat intelligence, network topology, business impact) to enrich understanding of the actual risk posed by each vulnerability.
Vulnerability behavioral analysis
AI-based approach that studies historical exploitation patterns to identify common behavioral characteristics of the most dangerous vulnerabilities.
Exposure score
Quantitative index measuring an organization's level of exposure to a specific vulnerability, combining accessibility, presence of critical assets, and potential attack vectors.
Critical Asset-Based Prioritization
Classification strategy that ranks vulnerabilities according to the value and strategic importance of affected assets, using contextual weighting algorithms.
Augmented Threat Intelligence
AI integration to enrich and automate threat intelligence analysis, enabling intelligent correlation between vulnerabilities and active attack campaigns.
Vulnerability Management Maturity Model
Structured assessment framework to measure an organization's ability to identify, prioritize, and remediate vulnerabilities in a proactive and intelligent manner.
Self-Adaptive Classification
AI system that dynamically adjusts its vulnerability classification algorithms based on feedback and the evolving threat landscape.
Contextualized Attack Vector
Intelligent analysis of possible exploitation paths taking into account the specific environment, existing security controls, and system configurations.
Hybrid Vulnerability Scoring
Approach combining static metrics (CVSS), predictive artificial intelligence, and contextual analysis to generate a more accurate and actionable risk assessment.
Reinforcement Learning for Prioritization
Use of RL algorithm to continuously optimize vulnerability prioritization strategy by adapting to the outcomes of previous decisions.
Intelligent Attack Surface Mapping
Automated process using AI to discover, map, and continuously evaluate potential entry points into the infrastructure for better prioritization.
Vulnerability Correlation Engine
AI system that establishes links between vulnerabilities, system configurations, and threat intelligence data to identify potential exploitation chains.