What is vulnerability threat intelligence?
Vulnerability threat intelligence is the practice of combining vulnerability assessment data with real-world threat information to understand which security weaknesses actually matter. This means you're not just looking at a list of vulnerabilities—you're seeing which ones attackers are actively exploiting right now.
TL;DR: Vulnerability threat intelligence combines CVE data with real-world exploitation evidence (CISA KEV, EPSS scores), network exposure, and asset criticality to prioritize which vulnerabilities to fix first—focusing remediation on threats that could actually harm your business.
This approach is also called threat-informed vulnerability management, vulnerability intelligence, or KEV-driven prioritization. Regardless of the term, the goal is the same: use real-world threat data to focus remediation efforts on vulnerabilities that pose actual risk to your organization.
Traditional vulnerability management often relies primarily on CVSS severity scores as the main prioritization signal, treating CVEs with the same score (e.g., all 9.8 criticals) as similarly urgent. This approach misses crucial context about which vulnerabilities attackers are actively exploiting in the wild. Vulnerability threat intelligence adds crucial context by showing you which vulnerabilities threat actors are targeting, which exploit code is available, and which attack techniques they're using. This helps you answer the question: Should I drop everything to patch this vulnerability, or can it wait?
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Why vulnerability threat intelligence matters
You face thousands of vulnerabilities across your infrastructure every day. Without threat intelligence, you're forced to either patch everything (impossible) or guess which vulnerabilities matter most (risky).
The old approach of patching based only on CVSS scores creates serious problems. You end up spending time fixing high-severity vulnerabilities that no one is exploiting while missing lower-scored vulnerabilities that attackers are actively using. CVSS-based prioritization can lead to significant over-patching. One academic study found that teams might need to address 60% of all vulnerabilities to capture just 20% of those actually exploited in the wild, demonstrating the inefficiency of severity-only approaches.
Vulnerability threat intelligence changes this by showing you what's actually happening in the wild. When you know which vulnerabilities attackers are targeting, you can focus your limited time and resources on the threats that could actually hurt your business. This shift from reactive patching to proactive, risk-based security makes your entire program more effective.
What is the threat intelligence lifecycle?
The threat intelligence lifecycle is a continuous, six-phase process that transforms raw data about potential cyber threats into refined, actionable intelligence
Read moreCore components of vulnerability threat intelligence
Effective vulnerability threat intelligence pulls together several key pieces to give you a complete picture of risk. Each component adds a layer of context that helps you make better decisions about which vulnerabilities to fix first.
Vulnerability data collection
This is your foundation—gathering detailed information about every CVE that could affect your systems. You pull data from sources like the National Vulnerability Database, vendor security advisories, and security bulletins to understand technical details, identify which systems are affected, and check if patches are available.
Threat intelligence integration
This layer adds the real-world context that makes vulnerability data actionable. You incorporate information from threat feeds, dark web monitoring, and security research to see which vulnerabilities attackers are actively exploiting. This tells you which CVEs are just theoretical risks versus which ones are being weaponized right now.
Contextual risk scoring
Moving beyond basic CVSS scores is where vulnerability threat intelligence really shines. Platforms with unified, graph-based context can automatically combine exploit likelihood (EPSS/KEV), external exposure, identity permissions, and data sensitivity to calculate real risk. You need to consider multiple factors to understand true risk:
Exploitability: Is exploit code publicly available or being traded in underground forums? Research consistently shows that a significant portion of exploited vulnerabilities have publicly available proof-of-concept exploits, making them easier for attackers to weaponize. This public availability dramatically increases risk compared to vulnerabilities requiring custom exploit development.
Exploit likelihood: Use the Exploit Prediction Scoring System (EPSS) alongside CVSS to predict the probability a vulnerability will be exploited within 30 days. Combine EPSS scores with CISA KEV status and external exposure data to create a multi-dimensional risk score that reflects real-world threat landscape.
Asset criticality: How important are the affected systems to your business operations?
Exposure level: Are vulnerable assets internet-facing or protected behind multiple layers of security?
Compensating controls: Do you have firewalls, access controls, or other security measures that reduce the risk?
Attack path analysis
This capability shows you how individual vulnerabilities connect to create dangerous attack chains. Graph-driven analysis excels here—connecting vulnerabilities, misconfigurations, identity paths, and data exposure to reveal exploitable routes an attacker could take from initial access to your crown jewels. By mapping these paths, you can see which vulnerabilities, when combined with other issues, create the most dangerous scenarios.
For example, during the Log4Shell incident (CVE-2021-44228), attack path analysis revealed how a single vulnerability in a logging library could be chained with cloud misconfigurations and excessive IAM permissions to reach production databases. Similarly, the MOVEit Transfer vulnerability (CVE-2023-34362) showed how file transfer vulnerabilities combined with network exposure created critical attack paths to sensitive data. These cases illustrate why KEV status, EPSS scores, and attack-path context matter more than raw CVSS severity.
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The vulnerability threat intelligence lifecycle
Vulnerability threat intelligence works as a continuous cycle that turns raw data into security actions. Each stage builds on the previous one to create a system that gets smarter over time.
Discovery and collection
Your program starts by gathering vulnerability information from every available source. This includes automated scanners that check your systems, exploit-probability models like EPSS (Exploit Prediction Scoring System) that predict which vulnerabilities are most likely to be exploited, and threat intelligence feeds that track active attacker campaigns. This creates a complete picture of your vulnerability landscape.
Analysis and enrichment
Raw vulnerability data doesn't tell you much on its own. In this stage, you add crucial context like whether exploit code exists, which threat groups are interested in the vulnerability, and how it's been exploited in the past. This transforms basic CVE information into intelligence you can actually use.
Prioritization and risk assessment
Now you evaluate which vulnerabilities pose the greatest actual risk to your organization. You look at factors like active exploitation in the wild, potential business impact, and whether attack paths exist that could lead to your critical assets. This creates a prioritized list that focuses your team's efforts where they matter most.
Code-to-cloud traceability helps route fixes to the right owner fast, reducing mean time to remediation without flooding teams with noise. When you can trace a runtime vulnerability back to the specific code commit and developer, remediation becomes targeted rather than broadcast.
Remediation and mitigation
Based on your risk assessment, you take action to address the most critical vulnerabilities. This might mean applying patches, updating software, or implementing compensating controls like additional access restrictions. Speed matters—in Q1 2025, 28.3% of exploited CVEs were observed being actively exploited in the wild within one day of CVE publication. This rapid exploitation window means teams must prioritize threat-informed patching to stay ahead of attackers. The key is focusing on fixes that eliminate real risk rather than trying to patch everything.
Feedback and improvement
After you remediate vulnerabilities, you monitor the results to see what worked and what didn't. This feedback helps you refine your prioritization models and response strategies over time. Your program continuously adapts based on what you learn from each cycle.
Key capabilities and sources for effective vulnerability intelligence
Building a strong vulnerability intelligence program requires pulling data from multiple sources and developing the right analytical capabilities. You need both breadth of information and the tools to make sense of it.
Intelligence sources
Your program needs to tap into several types of information sources:
Commercial threat feeds: Curated intelligence from security vendors about emerging threats and active exploitation campaigns
Open source intelligence: Publicly available information from security blogs, research papers, and forums that reveal new vulnerabilities
Dark web monitoring: Underground forums where threat actors discuss and trade exploitation techniques
Internal telemetry: Data from your own security tools showing attempted exploits and suspicious activity
Government advisories: Alerts from agencies like CISA about actively exploited vulnerabilities requiring immediate attention. The CISA Known Exploited Vulnerabilities (KEV) catalog specifically lists CVEs confirmed to be exploited in the wild, often with mandatory remediation deadlines for federal agencies.
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Essential capabilities
To turn all this data into action, you need several key capabilities:
Automated correlation: Your system should automatically link vulnerability data with threat intelligence to identify dangerous combinations of risks
Real-time alerting: You need immediate notifications when new threats emerge targeting vulnerabilities in your environment
Historical analysis: Understanding past exploitation patterns helps you predict future threats and improve your defenses
Integration capabilities: Your intelligence platform must connect with existing security tools to create unified visibility
Ownership mapping and ticketing integration: Automatically route prioritized vulnerabilities to service owners with context-rich tickets that include remediation steps, affected assets, and business impact. Integration with Jira, ServiceNow, and Slack shortens mean time to remediation by eliminating manual triage.
Implementation challenges and best practices
Setting up vulnerability threat intelligence comes with real challenges. Understanding these obstacles and how to overcome them helps you build a program that actually works.
Common obstacles you'll face
You'll likely run into several issues when implementing vulnerability threat intelligence. Data overload hits first—the sheer volume of vulnerability and threat information from multiple sources can overwhelm your team. Context gaps create another problem because intelligence often lacks specific details about how vulnerabilities relate to your unique environment. As of Q1 2025, 25.8% of Known Exploited Vulnerabilities (KEVs) were still awaiting or undergoing analysis in NIST's National Vulnerability Database (NVD). This analysis lag highlights why teams can't rely solely on NVD enrichment for time-sensitive prioritization decisions.
Resource constraints affect most teams since you probably don't have unlimited staff to analyze intelligence and coordinate fixes. Tool sprawl makes things worse when you're using multiple disconnected security products that don't share information effectively.
Strategies that work
Start by establishing complete visibility into your assets—you can't protect what you don't know exists. Use platforms that automatically correlate vulnerability data with threat intelligence and your environment's context to surface real risks without manual work.
Create clear, documented workflows so everyone knows how to respond to different risk levels. Break down silos by giving vulnerability management, threat intelligence, and IT operations teams a shared platform and common data. Track metrics like mean time to remediation for critical vulnerabilities to prove value and find areas for improvement.
Map your vulnerability management processes to compliance controls to satisfy auditors and regulators. ISO/IEC 27001 control A.12.6 requires vulnerability management, SOC 2 CC7.1 addresses threat detection, and NIST SP 800-53 controls RA-5 and SI-2 mandate vulnerability scanning and remediation. For U.S. federal agencies and contractors, align with CISA Binding Operational Directive 22-01, which sets specific remediation timelines for KEV vulnerabilities.
Operationalization checklist
How to operationalize vulnerability threat intelligence in your enterprise:
Normalize asset and CVE data across all scanning tools into a single inventory with consistent identifiers
Enrich vulnerability findings with EPSS scores, CISA KEV status, and exploit availability from threat feeds
Integrate with ticketing systems (Jira, ServiceNow) and set SLAs by risk tier—for example, KEV vulnerabilities within 15 days, EPSS >0.7 within 30 days
Build dashboards tracking mean time to remediation for high-risk categories and percentage of KEV vulnerabilities patched within SLA
Close the loop with post-remediation validation scans to confirm fixes and prevent regression
Measuring success in threat-informed vulnerability management
You need to measure your program's effectiveness to justify investment and drive improvement. Good metrics focus on actual risk reduction rather than just counting patches.
Key performance indicators
Track how much your exploitable attack surface decreases over time—this shows whether you're actually eliminating the pathways attackers could use. Measure how often your prioritized vulnerabilities align with actual exploitation attempts to validate your approach.
Monitor response velocity by tracking time from vulnerability disclosure to remediation for different risk levels. Assess what percentage of your assets are covered by vulnerability scanning and threat monitoring to identify gaps.
Maturity indicators
A mature program shows clear shifts in how you operate. You move from reactively responding to incidents toward proactively preventing them through intelligence-driven patching. Security, IT, and development teams work from shared intelligence instead of operating in silos.
Your workflows evolve from manual analysis to automated risk scoring and prioritization. You regularly review and refine processes based on lessons learned from past events and emerging threats.
How Wiz transforms vulnerability data into actionable threat intelligence
The most effective vulnerability threat intelligence platforms bring these elements together—agentless coverage across all cloud workloads, graph-based context that reveals attack paths, and code-to-cloud traceability that routes fixes to the right owners. This combination lets you fix what matters first without drowning in vulnerability noise.
Wiz's Security Graph automatically connects vulnerabilities with attack paths, network exposure, and sensitive data to show which CVEs actually threaten your cloud environment. The platform creates a unified view that reveals exactly how an attacker could exploit weaknesses to reach your critical assets.
The Wiz Threat Center delivers real-time intelligence on emerging vulnerabilities and active exploitation, helping you prioritize patches based on actual threat activity instead of just severity scores. This intelligence updates continuously as new threats emerge and exploitation patterns change.
Wiz's agentless vulnerability scanning discovers all vulnerabilities across containers, virtual machines, and serverless functions without any performance impact. This eliminates blind spots and operational overhead while giving you the complete visibility needed for threat-informed decisions.
Attack path analysis shows how vulnerabilities combine with other risks to create exploitable pathways to critical assets. This graph-based approach reveals hidden relationships between vulnerabilities, misconfigurations, and excessive permissions that attackers could chain together.
Wiz integrates with threat intelligence feeds and security tools to automatically correlate threat data with vulnerability findings across your cloud and surface prioritized, attack-path-aware remediation recommendations. This means you see not just a list of CVEs, but a ranked queue of fixes that eliminate real attack paths to critical assets. Cloud-to-code correlation traces vulnerabilities in running workloads back to the source code repository and likely owner (where CI/CD integrations exist) for faster, more targeted fixes. This reduces mean time to remediation by routing issues directly to the teams who can fix them.
Request a demo to see how Wiz cuts vulnerability noise with agentless coverage across all cloud workloads, graph-based context that reveals exploitable attack paths, and code-to-cloud remediation that routes fixes to the right owners—so you can focus on threats that actually matter.