ThreatQuotient’s whitepaper presents a data-driven approach to risk-based vulnerability management using the ThreatQ platform. It addresses challenges in prioritizing vulnerabilities by integrating internal and external intelligence to calculate both impact and likelihood of exploitation. The ThreatQ DataLinq Engine automates data ingestion, normalization, correlation, and prioritization, providing actionable insights for remediation. Through real-world use cases, it demonstrates how organizations can automate CVE tracking, enrich vulnerability context, and focus resources on the highest risks. This approach enhances decision-making, streamlines workflows, and strengthens overall cybersecurity posture.

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