Turn configuration drift into a managed-service work queue—not an auto-fix button

Source facts: secure configuration management is a lifecycle

NIST SP 800-128 Update 1 describes security-focused configuration management as part of the system development lifecycle. It covers identifying and documenting configurations, establishing baselines, controlling changes, monitoring configuration, and assessing whether approved controls remain effective. A baseline is managed reference information, not merely the latest configuration a collector happened to observe.

CISA’s hardening and visibility guidance for communications infrastructure emphasizes secure configuration, centralized logging, monitoring for changes, strong administration, and the ability to detect unauthorized behavior. The NIST Cybersecurity Framework likewise connects configuration management with governance, protection, detection, and recovery.

Neither source says every difference should be reverted automatically. Drift can represent an approved emergency change, vendor update, generated identifier, site-specific requirement, failed rollout, manual error, or adversary action. An automatic repair made without current service context can remove a legitimate route, lock out administrators, interrupt production, erase evidence, or create a configuration loop.

DSE recommendation: convert drift evidence into governed work

Use automation to collect, compare, enrich, and verify. Reserve consequential remediation for a policy that considers service ownership, change authority, dependencies, and recovery.

Define the baseline object. Specify device or resource type, software or firmware family, site role, approved version, required controls, customer exceptions, owner, effective date, and source change record. Version baselines so the team can distinguish a new standard from unauthorized drift.

Collect defensibly. Authenticate collection, record target and collector identity, normalize output, timestamp it, protect sensitive values, and retain hashes or version references. Detect partial collections and offline assets instead of treating missing evidence as compliance.

Remove meaningless noise. Exclude counters, timestamps, randomized ordering, learned state, dynamic leases, ephemeral sessions, and secrets that should never enter the comparison store. Document every normalization rule so it cannot conceal a security-relevant change.

Classify differences. Separate expected deployment change, documented exception, stale baseline, failed enforcement, unknown modification, and urgent exposure. Enrich findings with asset criticality, customer, maintenance window, recent tickets, identity activity, internet exposure, and rollback readiness.

Create an owned queue. Give each actionable difference a severity, service owner, due date, evidence, proposed disposition, and customer impact. Link duplicates without discarding affected assets. Escalate aged unknowns and changes to identity, remote access, logging, backup, or security controls.

Control remediation. Permit automatic repair only for well-tested, low-impact, reversible cases with explicit authorization. Require approval for network paths, identity policies, production services, destructive commands, or broad changes. Preserve the pre-change state and define stop conditions.

Verify and learn. Recollect after remediation, test the business service, confirm security telemetry, and close the work only when the intended state is proven. Update the baseline when the change is legitimate and review recurring drift for process or automation defects.

Before relying on the queue in production, run controlled exercises. Make one authorized change that should be recognized, one unapproved but harmless change that should escalate, one ephemeral value that should be ignored, and one failed collection that must remain unknown rather than pass. Confirm the workflow preserves the original evidence, identifies the correct customer and owner, opens only the expected work, blocks an unauthorized repair, and records verification after an approved remediation. Repeat the exercise when collection, normalization, or automation logic changes.

Factual boundary: Drift is not synonymous with compromise, and a clean comparison does not prove a system is secure. Collection can be incomplete, the baseline can be wrong, and an attacker may alter both the target and a poorly protected management plane. Product-specific rollback and validation remain essential.

Measure monitored coverage, collection failures, meaningful differences per asset, unknown-drift age, unauthorized changes, auto-remediation reversals, repeat findings, and verification failure. The managed-service value is not a dashboard full of red differences. It is a reliable path from changed evidence to an accountable decision and a verified operating state.

Official references

NIST, Guide for Security-Focused Configuration Management of Information Systems, SP 800-128 Update 1.

CISA, Enhanced Visibility and Hardening Guidance for Communications Infrastructure.

NIST, Cybersecurity Framework.