Unified Control Mapping: Building Reusable Compliance Components

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Compliance management gets complicated fast. Every framework has its own language, numbering, and evidence expectations. Organizations chasing multiple certifications end up maintaining separate control sets for FedRAMP, CMMC, SOC 2, ISO 27001, and NIST 800-53. Each one needs its own policies, proof, and workflows.

That creates a lot of redundant work. Teams rewrite the same procedures under different names. Evidence gets collected multiple times for the same control intent. Auditors review overlapping data that could have been reused.

Unified control mapping solves that problem. It turns scattered frameworks into a single, reusable system of record.

 

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Implementing NIST SP 800-172 Controls

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The journey to CMMC Level 3 represents the highest level of cybersecurity maturity under the CMMC framework. Unlike Levels 1 and 2, which focus on FCI and CUI, respectively, Level 3 targets Advanced Persistent Threats (APTs). That means more extensive security, defined in NIST Special Publication 800-172.

For organizations that support critical programs or handle high-value assets for the Department of Defense, achieving Level 3 is imperative. But what does it take to implement the enhanced controls from NIST SP 800-172, and how do they fit into the broader CMMC ecosystem? This article explores that challenge and provides a practical roadmap for organizations preparing to meet it.

 

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How To Automate Evidence Collection Across Frameworks

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Manual evidence collection slows teams down and introduces risk. Every audit cycle turns into a scramble for screenshots, exports, and documents. Each framework adds another layer of repetition. The same control might need to be proven three or four times in slightly different ways. The result? Wasted time, outdated evidence, and frustrated compliance teams. 

There’s a better way to manage evidence: automate it and connect it all to a single source of truth. This approach turns a reactive process into a continuous, reliable, scalable system.

 

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