From Static Scores to Smart Defense: The Rise of Risk-Based Vulnerability Management (RBVM)

Traditional vulnerability scores only offer a snapshot in time. Risk-Based Vulnerability Management (RBVM) uses dynamic threat intelligence and AI to prioritize what matters most—helping security teams focus resources where they count. Here’s why it’s becoming the go-to strategy for modern digital defense.

What is Risk-Based Vulnerability Management?

Risk-based vulnerability management programs (RBVM) have become a natural progression towards a risk-based approach by associating the critical impact of vulnerabilities and establishing the highest and most dynamic prioritization score based on additional elements. These additional elements include the use of AI-based threat intelligence that reflects the potential cybersecurity impact of the organization’s current internal and external digital landscape.

Augmenting CVSS with RBVM - An Important Progression

Before RBVM, cybersecurity vendors, security teams, and industry analysts used the more traditional Common Vulnerability Scoring System (CVSS) in their vulnerability management solutions. CVSS associated the threat scoring based on a snapshot of the risk to critical assets. This method remains a global standard for risk scoring and traditional vulnerability management.

CVSS addresses many critical areas of vulnerability management, including providing a standardized, consistent, proven, and mature model to assign a score of 0 to 10 to a specific vulnerability. This scoring strategy helps organizations establish a basic level of prioritization and risk level.

RBVM’s dynamic scoring becomes far more fluid, based on real-time telemetry processing, and provides more accurate and actionable insights while leveraging a risk-based prioritization strategy. This approach to cybersecurity posture management helps organizations establish a more straightforward strategy for resolving vulnerabilities.

RBVM aligns strongly with organizations that are moving forward with artificial intelligence (AI) and machine learning (ML) to enhance their incident response and remediation capabilities.

Importance of Dynamic Prioritizing Risks over Traditional Vulnerability Scoring

CVSS relies heavily on data based on the current state of a vulnerability. The higher the risk of exploiting the vulnerability, the greater the score. However, CVSS is a static metric, and even a higher risk score doesn’t guarantee that this vulnerability will become exploitable.

However, RBVM has several additional input functions to help create the current score with even greater accuracy. RBVM dynamically adjusts to risk score based on real-time threat intelligence and remediation efforts. The dynamic vulnerability management strategy also plays a critical role in how organizations evaluate the risk of their entire attack surface.

This strategy of dynamic risk combined with prioritization promotes a positive impact on where the organization needs to allocate funds for remediation, replacement, and enhancing current cybersecurity tools and processes.

Key Components of RBVM

RBVM leverages additional tools and information sources to help determine the current scoring. These additional elements help provide a far more updated and accurate risk posture.

• Integration of AI-Based Threat Intelligence
  AI-powered threat intelligence is quickly becoming the gold standard for security teams, business leaders, and investors. Threat intelligence, powered by AI processes, can process far greater amounts of data within its large Language Model (LLM). As LLM and AI agents become more consumed, this strategy will help organizations adjust to a more RBVM-type scoring posture.

• Comprehensive Risk Scoring Method
  RMVB scoring considers the importance of the asset to the organization, the relevance of the vulnerability risk to the organization, the likelihood of the asset being targeted in a cyberattack, and the potential business impact of a successful attack.
  Yes, assets based on CVSS may have a high score due to vulnerability risk; however, if the associated vulnerability is related to low-value assets, engineers’ efforts to remediate are better spent on critical business assets within the enterprise. Hence, the value of dynamic priorization adjustment within the RBVM framework.

• Automation
  AI and ML automation capabilities for remediation, as well as executing automated risk assessments, reduce human error and false positives. Time savings play a decisive role in the RBVM strategy. By leveraging automated vulnerability scanning, organizations can conduct real-time risk assessments, remediate issues as needed, and reassess the risk without requiring human interaction. By executing a post-remediation vulnerability assessment, RBVM systems can update the current risk scoring to reflect the security posture.

What are The Benefits of Leveraging RBVM?

Leveraging AI-powered threat intelligence data, automation, and more dynamic scoring embedded within RBCM helps organizations in several ways:

• Improved Accuracy
  As AI becomes further embedded within threat intelligence platforms, organizations will assign a dynamic risk score to their more critical digital assets based on more advanced dataset learning.

• Greater Visibility of Vulnerability Risk
  RBVM provides the means to help provide 100% visibility across the organization’s enterprise environment. This dynamic risk scoring approach integrates with AI-based threat intelligence, asset inventory, and remediation, providing the organization with significantly greater visibility and risk reduction.

• Continuous Change to the Threat Posture
  CVSS provided a snapshot of the risk posture at a given time. RBMV helps reassign new scores based on updated AI-based threat intelligence, recent remediation steps, and a reevaluation of the risk to the organization and its overall posture. One strength of RBVM is its ability to help the organization quickly determine its security posture based on changes to its attack surface.
  For example, if the organization has recently introduced a new application with no current security patches, introducing this new digital asset now becomes a higher priority due to the apparent security risk. RBVM tools will identify the new asset as a higher-priority risk and automatically adjust the priority level.
  This dynamic change in priority requires prompt remediation against the new highest-priority asset. This capability is a true value-add of RBVM.

• Greater Resource and Financial Efficiency Gains
  RBVM helps organizations invest their time in the highest-priority security threats within their enterprise. This level of prioritization helps the organization focus its attention on cyber threats and vulnerability severity by asset, and invest less in low-risk issues. This insight into the level of risk in the highest areas also means the organization can best use its human capital and SecOps resources’ time.

Challenges in RBVM Implementation

RBVM, like any other risk management strategy, has its challenges. For RBVM to work, organizations need to have the means to collect and process large amounts of data. The collection and processing of large amounts of data creates the possibility of prejudicial outputs. Incomplete data telemetry or outdated information also plays into the challenges with RBVM.

RVBM also relies on integration with asset inventory tools, remediation solutions, and automated incident response functions. Organizations need qualified engineers to manage this functionality.

Organizations that cannot stay current with the inventory of devices, cloud instances, applications, and networking devices will hinder their ability to leverage their RBVM to its full capability.

The Role of AI-Powered Threat Intelligence

AI-powered threat intelligence is ultimately the most critical piece in the RBVM journey for an organization. The association of a dynamic risk score relied on the most updated and relevant threat intelligence information to help set the most accurate risk prioritization. Organizations often lack the resources to remediate every vulnerability, partly because of the sheer volume of vulnerabilities. The dynamic risk factoring helps them apply their human capital and financial resources to their most critical digital assets.

These assets are linked to the organization’s ability to meet various compliance requirements.

Why Overwatch?

Security operations and risk management teams determined to move ahead with an RBVM strategy need to ensure their choice of AI-based threat intelligence source comes from a firm with the highest level of integrity, demonstrates the highest level of transparency and ethics, and stands behind its data sources.

Overwatch is a company built on those founding principles. AI-powered threat intelligence led by a group of talented and experienced engineers to create the gold standard.

Moving with an RBVM strategy or looking to upmarket your current threat intelligence capabilities? Click here to schedule a demonstration of the Overwatch platform today!