AC-4(27): Redundant/Independent Filtering Mechanisms

AC-4(27): Redundant/Independent Filtering Mechanisms requires you to use two independent content-filtering controls (or equivalent independence) for each data type that crosses between different security domains, so one failure or bypass does not result in prohibited data transfer ¹. Operationalize it by mapping every cross-domain flow, defining allowed content rules per data type, and proving both filters enforce those rules with test evidence.

Key takeaways:

• Apply the control only where information transfers between different security domains, then treat each “domain crossing” as a scoped system boundary.
• “Redundant and independent” means a second, separately administered enforcement point with different failure modes, not just a second rule in the same tool.
• Your audit pass depends on evidence: architecture, rule sets, independence rationale, and repeatable test results per data type.

This requirement shows up when you have real segmentation: separate enclaves, classifications, tenants, regulated environments, or restricted networks, and data must move between them. In those situations, a single content filter becomes a single point of failure. AC-4(27) asks you to design transfers so two independent filtering mechanisms must both “agree” before content crosses, and you do that for each data type you allow ¹.

For a Compliance Officer, CCO, or GRC lead, the fastest path is to treat this like a repeatable control pattern: (1) enumerate cross-domain flows, (2) define permitted data types and constraints, (3) implement two independent filters per permitted type, and (4) produce evidence that proves the controls operate as designed under realistic test cases. The hard part is not buying tooling; it’s preventing “false independence” (two filters that share the same policy engine, admin plane, or failure mode) and documenting why your design meets the intent. AC-4(27) is assessed as part of boundary protection and information flow enforcement under NIST SP 800-53 Rev. 5 ².

Regulatory text

Requirement (verbatim): “When transferring information between different security domains, implement content filtering solutions that provide redundant and independent filtering mechanisms for each data type.” ¹

What the operator must do:

• Identify every transfer path that crosses security domains (for example, low-trust to high-trust, tenant to tenant, corporate network to regulated enclave, dev to prod, internet to internal restricted zone).
• For each data type you permit across that boundary (examples: files, email, web uploads, APIs, database replication, logs), implement two filtering mechanisms that are redundant (both enforce policy) and independent (a compromise, misconfiguration, outage, or bypass of one does not automatically defeat the other) ¹.
• Maintain evidence that the two mechanisms exist, are configured for each data type, and are tested.

Plain-English interpretation

You need “two gates” for content moving between domains, and each gate must work even if the other gate fails. Independence is the point: auditors will ask whether a single administrative mistake, a single exploit, or a shared service dependency could knock out both filters at once.

Practical translation:

• If one mechanism is a network DLP inspection point, the second can be an application-layer validator that rejects disallowed uploads.
• If one mechanism is an email security gateway, the second can be endpoint DLP or a secure file transfer service that scans and enforces classification rules before release.
• If the only “redundancy” is a second rule in the same appliance, you likely do not have independence.

Who it applies to

Entity types (typical):

• Federal information systems and contractor systems handling federal data aligned to NIST SP 800-53 control baselines ².

Operational contexts where it becomes in-scope:

• Cross-domain solutions (CDS) or guarded transfers between enclaves.
• Segmented networks where one side has materially different trust requirements (regulated zone, classified network, OT/ICS, PCI CDE-like segmentation, research enclave).
• Multi-tenant SaaS with strict tenant-to-tenant separation where “domain” is a tenant boundary and transfers are explicitly brokered.
• Mergers, shared services, or third-party connectivity where a partner network is treated as a separate domain.

Quick scoping test (use this in intake):

• Does the transfer cross a boundary where you claim different security policy applies? If yes, AC-4(27) likely applies.
• Do you allow more than one data type across it? If yes, you must show redundant/independent filtering for each allowed type.

What you actually need to do (step-by-step)

1) Build the cross-domain flow inventory (authoritative list)

Create a register with one row per domain crossing:

• Source domain, destination domain, and owner.
• Transport/protocol (HTTP/S, SMTP, SFTP, message bus, API, database link).
• Allowed data types and business purpose.
• Existing controls in the path.

Deliverable: Cross-Domain Information Flow Register tied to your system boundary documentation and network diagrams.

2) Define “data type” categories you will enforce

Auditors will accept your categories if they are clear and mapped to enforcement points. Common categories:

• File transfers (documents, archives)
• Email content and attachments
• Web uploads/downloads
• API payloads (JSON/XML), messages, events
• Database replication/export
• Logs/telemetry

Deliverable: Data Type Taxonomy for Domain Crossings with examples and owners.

3) Define allow/deny rules per data type (what “content filtering” means for you)

For each crossing and data type, document enforceable rules such as:

• Allowed MIME types / file extensions, and archive handling rules.
• Max file size, encryption requirements, and password-protected file handling.
• Malware scanning requirements and verdict handling.
• Sensitive data patterns (regulated identifiers, secrets) and blocking/quarantine workflows.
• Structured payload schema validation for APIs (required fields, prohibited fields, content constraints).
• Content classification tags and labeling rules if you use labeling.

Deliverable: Information Flow Policy Matrix (crossing × data type × rule set).

4) Design two independent filtering mechanisms per data type

Independence is where most implementations fail. Use this checklist when selecting mechanisms:

Independence checklist (document your answers):

• Separate enforcement components (not just two policies inside one engine).
• Separate admin access paths and change control (ideally different roles or approval steps).
• Different failure modes (one failing “open” does not cause the other to fail open).
• Independent logging and alerting paths (so you can detect bypass).
• Where possible, diverse technology stacks (not required, but helps your argument).

Common patterns that usually satisfy the intent:

• Network gateway content inspection + application-layer validation (server rejects content even if gateway misses it).
• Secure transfer broker with scanning + endpoint DLP preventing exfiltration from destination environment.
• API gateway schema validation + service-side input validation and content controls.

Deliverable: Filtering Architecture Diagram that shows both controls in-line (or otherwise enforced) for each data type crossing ¹.

5) Implement change control and configuration management for both filters

You need governance as much as technology:

• Document control ownership for each mechanism.
• Require ticket-based changes, peer review, and approval for rule changes.
• Record emergency change procedures and after-action review steps.

Deliverable: Filtering Mechanisms SOP (operations runbook) and change records.

6) Test the filters with “known bad” and “edge” cases per data type

Testing must demonstrate the redundancy and independence:

• Confirm each filter blocks prohibited content on its own.
• Confirm one filter’s misconfiguration does not automatically disable the other.
• Confirm logs are generated in each system and can be correlated to a transfer attempt.

Example test cases:

• File: EICAR test file (if permitted), macro-enabled docs, nested archives, password-protected archives.
• API: payload with prohibited fields, oversized payload, invalid schema.
• Email: attachment with prohibited extension, embedded links, sensitive pattern text.

Deliverable: Content Filtering Test Plan + test results per domain crossing and data type.

7) Operational monitoring and incident handling

Define:

• Alerts for policy hits, repeated violations, and filter service outages.
• A bypass exception process with compensating controls and time-bound approvals.
• Incident playbooks when a prohibited transfer is detected.

Deliverable: Monitoring rules, alert samples, and incident playbook aligned to the crossings.

Required evidence and artifacts to retain

Keep these ready for assessment sampling:

• Network/data flow diagrams showing security domains and transfer paths.
• Cross-Domain Information Flow Register (authoritative inventory).
• Information Flow Policy Matrix (allowed data types and filtering rules).
• Configuration exports or screenshots for both filtering mechanisms per data type.
• Access control list of admins for each mechanism and evidence of role separation where applicable.
• Change tickets and approvals for rule updates.
• Test plan and test results demonstrating both mechanisms enforce policy.
• Centralized log samples showing events from each filter and correlation to transfer attempts.
• Exception register for temporary bypasses, with compensating controls and expiration.

Practical tip: Daydream can track AC-4(27) as a requirement mapped to a single control owner, an implementation procedure, and a recurring evidence list so you are not rebuilding the evidence package each assessment cycle ¹.

Common exam/audit questions and hangups

Expect questions like:

• “Show me all transfers between security domains.” (They will sample what you forget.)
• “For this crossing, what are your allowed data types, and where are those rules documented?”
• “Explain why these two filters are independent. What shared dependencies exist?”
• “What happens if Filter A is down? What happens if Filter B is down?”
• “Prove that each filter blocks the prohibited file/API payload/email on its own.”
• “Show evidence of periodic testing and change control for both mechanisms.”

Hangup to preempt: auditors often reject “two layers” that are both managed through one console with one policy pipeline and one failure mode. Document your independence rationale explicitly.

Frequent implementation mistakes and how to avoid them

Mistake 1: Treating “redundant” as “HA pair”

High availability reduces downtime; it does not create a second, independent policy enforcement point.
Avoidance: keep HA for resilience, but still add a second enforcement mechanism that can block content independently.

Mistake 2: Two rules in the same tool

If an attacker bypasses the tool, both rules fail.
Avoidance: use different enforcement planes (for example, gateway + application, gateway + broker, broker + endpoint).

Mistake 3: Independence exists technically, but not operationally

Same admin group, same change window, same CI/CD pushes, same misconfiguration risk.
Avoidance: enforce approval workflows, separate roles where feasible, and keep an exception register.

Mistake 4: Data types are undefined

Teams say “we filter content,” but cannot explain what content types exist on the crossing.
Avoidance: define a data type taxonomy and map each crossing to explicit types and rules.

Mistake 5: No repeatable testing

Controls drift; filters get disabled for troubleshooting; rules erode under pressure.
Avoidance: require a periodic test cadence tied to change control and assessment readiness.

Enforcement context and risk implications

No public enforcement cases are provided in the supplied sources for AC-4(27). Your real exposure is assessment failure or authorization friction: if you cannot prove independent redundant filtering for each data type, assessors can record a control deficiency against information flow enforcement ¹. Operationally, gaps raise the likelihood of data spillage across domain boundaries, which then triggers incident response, containment, and customer/regulator reporting obligations depending on your environment.

A practical 30/60/90-day execution plan

First 30 days (stabilize scope and decisions)

• Name a single control owner and backups for AC-4(27).
• Build the Cross-Domain Information Flow Register.
• Agree on your data type taxonomy and define “data type” for your environment.
• Identify the current “Filter #1” for each crossing and document gaps against “Filter #2.”
• Write the independence criteria you will use to approve designs.

Day 31–60 (implement and document the second mechanism)

• For each high-risk crossing, implement the second filtering mechanism per allowed data type.
• Formalize SOPs: rule management, outages, exceptions, emergency changes.
• Configure centralized logging for both filters, and create correlation views per crossing.
• Capture configuration baselines and access control evidence for both mechanisms.

Day 61–90 (prove operation and make it audit-ready)

• Run test cases per data type and crossing; store results with timestamps and artifacts.
• Execute a tabletop for bypass/exception handling and validate approvals and expirations.
• Perform an internal control walkthrough: pick one crossing and answer every “audit question” above with evidence.
• In Daydream, map the requirement to the owner, procedure, and recurring evidence so ongoing compliance becomes a scheduled workflow, not a scramble ¹.

Frequently Asked Questions

What counts as “different security domains” for AC-4(27)?

Any boundary where you enforce materially different security policy or trust assumptions can qualify, including segmented enclaves, tenant boundaries with controlled transfer, or partner connectivity. Treat each explicit boundary crossing as in-scope if content is transferred ¹.

Does an HA pair of the same content filter meet the “redundant/independent” requirement?

HA improves availability but does not create independence because both nodes share the same policy engine and bypass conditions. You still need a second enforcement mechanism with different failure modes ¹.

Can the second mechanism be a manual review step?

Manual review is rarely strong enough as a “filtering mechanism” for all data types because it is inconsistent and hard to prove at scale. If you use manual checks, constrain them to narrow exception paths, and keep audit-grade records for each approval.

How do we show “independence” to an assessor without overengineering?

Document the independence rationale: separate components, separate admin controls, separate logs, and what happens when one fails. Then prove it with tests where one mechanism is misconfigured or unavailable and the other still blocks prohibited content.

What if we only transfer one data type across the boundary (for example, an API)?

Then focus on two independent controls for that one data type, such as gateway validation plus service-side validation and content restrictions. Make the “per data type” argument explicit in the policy matrix ¹.

How should third parties be handled if they operate one side of the domain crossing?

Treat third-party connections as domain crossings and require contractually enforced controls, technical integration requirements, and evidence rights. If the third party operates a filter, you still need to show redundant/independent filtering across the end-to-end transfer path under your risk acceptance process.

Footnotes

1. NIST SP 800-53 Rev. 5 OSCAL JSON

2. NIST SP 800-53 Rev. 5