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Blog Matthew Martin Blog Matthew Martin

From "What" to "What Now?": How to Turn Security Assessments into Action

Security assessments don’t fail because the findings are wrong—they fail because execution stalls. Too often, organizations invest in audits and maturity reviews only to let the final report collect dust. Real progress doesn’t start with a checklist; it starts with alignment, prioritization, ownership, and change management. When recommendations are treated as strategic initiatives—not side tasks—security moves from insight to impact.

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Blog Michael Forbiteh Blog Michael Forbiteh

Why Most GRC Programs Fall Short, And How to Build One That Actually Works

Many organizations believe their GRC program is strong—until an audit, breach, or compliance failure exposes fragmented policies, unclear ownership, and manual processes that can’t keep pace with evolving risk. By aligning to the right frameworks, translating them into actionable controls, automating key workflows, and building real-time visibility, GRC can shift from a reactive burden to a strategic driver of resilience and trust.

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Blog Chad Parnin Blog Chad Parnin

Together, We Secure the State: A Leader's Guide to AppSec & CloudSec Synergy

Application Security and Cloud Security are strongest when they work together—not in silos. In this post, we explore how AppSec and CloudSec collaboration reduces risk, accelerates secure cloud deployments, and strengthens enterprise security through shared ownership, aligned metrics, and leadership-driven teamwork. A practical guide for CISOs, CIOs, and security leaders looking to build resilient, cloud-ready security programs.

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Blog Matthew Martin Blog Matthew Martin

When AI Gets Phished: What Machine Learning Supply Chain Attacks Can Teach Us About Trust

As organizations rush to adopt AI, a new question is emerging alongside performance and accuracy: can we actually trust our models? In this blog, Matthew Martin explores how machine learning supply chain attacks mirror familiar human and software risks—and why treating AI models like new employees, with proper vetting, monitoring, and governance, is critical to building secure, trustworthy AI systems.

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