Your Critical Vulnerabilities Might Not Be Your Biggest Risk

Security teams have become exceptionally talented at finding vulnerabilities. Now, it’s time to turn our attention to optimizing the process for determining which of those vulnerabilities actually create a path to compromise. A critical vulnerability may look alarming on a scanner report, but if it sits behind strong segmentation, identity controls, and other defenses that prevent an attacker

The article discusses how traditional vulnerability management often over-prioritizes technically 'critical' issues that are effectively mitigated by strong segmentation, identity controls, and layered defenses, and instead advocates focusing on vulnerabilities that actually create realistic paths to compromise. This is a general cybersecurity risk management perspective and does not report specific AI systems, models, or agents being targeted. RealGround’s analysis is that the same path-to-compromise thinking should be applied to AI supply chains and AI infrastructure, ensuring organizations prioritize weaknesses that expose model hosting, orchestration platforms, or data pipelines rather than only scanner-rated criticals. Practically, this means using AI Security Readiness Assessments and AI Supply Chain & SBOM Advisory to map how vulnerabilities in underlying platforms, dependencies, and integrations could lead to AI system compromise, even when individual CVEs look well-defended in isolation.