They should treat drift as a continuous control problem, not a periodic audit finding. That means comparing live settings to approved baselines, assigning owners to every exception, and removing temporary changes before they become normal operating state. In constrained environments, automated detection matters more because manual review rarely keeps pace with change.
Why This Matters for Security Teams
In municipal environments, configuration drift is not just an administrative nuisance. It can expose citizen data, interrupt public services, and create audit gaps across endpoints, servers, cloud tenants, and legacy systems that are expected to remain stable for years. NIST’s NIST Cybersecurity Framework 2.0 treats ongoing asset and control management as an operational discipline, which is the right lens for cities where change often happens through emergency fixes, vendor workarounds, and staff turnover.
The real problem is that drift accumulates quietly. A temporary firewall exception becomes permanent, a local admin account stays enabled after a project ends, or a baseline configuration is bypassed to keep a critical service online. NHIMG’s Ultimate Guide to NHIs — Regulatory and Audit Perspectives is useful here because many municipal changes are introduced by non-human identities such as service accounts, automation jobs, and integration tokens rather than by named staff. In practice, many security teams encounter drift only after an outage, a failed audit, or an access review has already missed it.
How It Works in Practice
Managing drift well starts with a baseline that is both approved and testable. Security teams should define desired state for key systems, then continuously compare live configuration against that state. For municipal environments, this is often more effective than relying on periodic audits because small exceptions spread quickly across departments, vendors, and on-premises infrastructure.
A practical workflow usually includes:
- Baseline critical systems by function, not just by platform, so firewalls, servers, cloud subscriptions, and identity controls each have a clear approved state.
- Assign an owner to every exception, including emergency changes and vendor-required deviations, with an expiry date attached.
- Use automated detection for drift in settings that affect access, logging, patching, and secrets handling.
- Track non-human identity activity separately where service accounts, API keys, and automation scripts can change configurations without a human user present.
- Review and remove temporary changes before they become accepted operating practice.
That approach aligns with the control themes in Top 10 NHI Issues, especially where excessive privilege and poor visibility make drift harder to spot. It also fits the guidance direction in CISA Zero Trust Maturity Model, because drift control depends on verifying state continuously rather than assuming last month’s approval still holds. When teams can, policy-as-code and configuration management tools should be tied to ticketing so every change has a business reason, a reviewer, and a rollback path. These controls tend to break down in municipalities with fragmented legacy ownership because local exceptions are often approved informally and never re-enter the central record.
Common Variations and Edge Cases
Tighter drift control often increases operational overhead, requiring organisations to balance stronger consistency against the need to keep essential services running. That tradeoff is especially visible in municipalities that support emergency response, public safety, utilities, or school networks, where downtime tolerance is low and some deviations may be justified.
Current guidance suggests treating these cases as managed exceptions rather than permanent policy changes. For example, a vendor patch window, a legacy protocol needed by a public records system, or a temporary change during a major incident should be documented, time-boxed, and revisited. The key is not to eliminate all drift instantly, but to distinguish approved variance from uncontrolled change.
This is also where governance often matters more than tooling. If department owners can introduce changes without central visibility, automated drift detection will still find problems but not necessarily prevent them. Conversely, very strict baselines can slow service delivery if they are written without operational input. NHIMG’s NHI Lifecycle Management Guide is relevant because municipal drift frequently involves credentials and automations that outlive the process that created them. The strongest programs use review cycles, exception expiry, and owner accountability together. Best practice is evolving, but there is no universal standard for this yet across all municipal system types.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Non-Human Identity Top 10 address the attack and risk surface, while NIST CSF 2.0 and NIST AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST CSF 2.0 | GV.OC-01 | Drift control depends on current operational context and ownership. |
| OWASP Non-Human Identity Top 10 | NHI-03 | Drift often appears through unmanaged secrets, keys, and service accounts. |
| NIST AI RMF | Municipal automation and AI-enabled controls need continuous monitoring for state changes. |
Apply continuous monitoring and governance checks to detect unauthorized configuration changes.
Related resources from NHI Mgmt Group
- How should security teams manage configuration drift in Microsoft 365 and Entra ID?
- How should security teams prioritise NHI remediation in cloud environments?
- How should security teams govern non-human identities in cloud environments?
- How should security teams think about a compromised integration like Drift?
Deepen Your Knowledge
Reviewed and updated by the NHIMG editorial team on July 8, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org