SI-10(5): Restrict Inputs to Trusted Sources and Approved Formats

To meet the si-10(5): restrict inputs to trusted sources and approved formats requirement, you must enforce technical and procedural gates so your systems only accept data from approved, authenticated sources and only in explicitly allowed formats. Operationalize this by inventorying input paths, defining allowlists (sources and schemas), implementing validation and blocking controls, and retaining repeatable evidence of enforcement ¹.

Key takeaways:

• Identify every “input surface” (APIs, files, web forms, message queues, ETL, admin consoles) and assign owners.
• Enforce allowlists for both who can send inputs (trusted sources) and what they can send (approved formats/schemas).
• Keep audit-ready evidence: configuration, test results, logs, exceptions, and change approvals mapped to SI-10(5).

SI-10(5) is one of the fastest ways to reduce avoidable security failures tied to bad inputs: malicious payloads, malformed files, unexpected encodings, untrusted integrations, and “temporary” ingestion paths that become permanent. The control’s intent is straightforward: systems should not accept arbitrary information inputs. Instead, you define which sources are trusted and which formats are permitted, then you enforce those restrictions in runtime controls and governance.

For a Compliance Officer, CCO, or GRC lead, the practical challenge is scoping. “Information inputs” includes more than customer-facing forms. It covers partner feeds, third-party integrations, batch uploads, SFTP drops, webhook events, mobile clients, administrative import tools, and internal pipelines where one service becomes another service’s “source.” The good news: you can operationalize SI-10(5) with a small set of repeatable patterns—allowlists, strong authentication, schema validation, file-type controls, and exception management—paired with consistent evidence capture.

This page gives requirement-level implementation guidance you can hand to Engineering, Security, and platform owners, while keeping assessment readiness front and center ².

Regulatory text

NIST SI-10(5) (enhancement) excerpt: “Restrict the use of information inputs to {{ insert: param, si-10.05_odp.01 }} and/or {{ insert: param, si-10.05_odp.02 }}.” ¹

Operator meaning: you must configure and manage systems so they only accept inputs from approved/trusted sources and/or in approved formats. Because the excerpt uses parameters, your implementation must explicitly define what “trusted sources” and “approved formats” mean for your environment, then enforce them consistently across all input channels ¹.

Plain-English interpretation (what the control is asking)

SI-10(5) requires two concrete decisions and one enforcement mechanism:

1. Trusted sources: Define which identities, systems, networks, integrations, and third parties are allowed to submit data to each input surface. “Trusted” should be anchored in authentication, authorization, and provenance. “It’s on our VPN” is rarely enough by itself.
2. Approved formats: Define which content types, schemas, field constraints, encodings, file types, and protocol expectations are allowed. “JSON” is not a format definition; a schema (and limits) is.
3. Restrict use: Put technical controls in place so nonconforming inputs are blocked or quarantined, not just detected after the fact. SI-10(5) is a restriction control, not a logging-only control ¹.

Who it applies to

Entities

• Federal information systems and contractor systems handling federal data implementing NIST SP 800-53 Rev. 5 controls ¹.

Operational contexts (where it shows up in real programs)

• API platforms (external and internal), including partner APIs and webhooks.
• File ingestion (SFTP, object storage drops, email-to-ticket attachments, “upload CSV” admin tools).
• Data pipelines (ETL/ELT jobs, message queues, streaming topics).
• Endpoint and agent telemetry ingestion.
• IAM and admin workflows that import users, groups, entitlements, or configurations.
• Third-party integrations where a vendor/partner system becomes an input source.

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

Use this as an implementation checklist. Assign a control owner (Security/GRC) and technical owners (API gateway, app teams, data engineering) so evidence is repeatable ¹.

Step 1: Inventory and classify input surfaces

Create (or update) an “Input Surface Register” that lists:

• System/application name and environment (prod/non-prod)
• Input type (API endpoint, file drop, queue, UI form, admin import, integration)
• Source categories (customer, employee, service-to-service, third party)
• Data sensitivity handled on that path
• Owner and on-call team

Practical scoping rule: if data crosses a trust boundary (internet, partner network, another account/tenant, another service), treat it as an SI-10(5) in-scope input.

Step 2: Define “trusted sources” per input surface

For each input surface, document an allowlist in operational terms:

• Identity requirements: mTLS client certs, OAuth client credentials, signed JWTs, workload identity, or other authenticated identities tied to authorization.
• Authorization boundaries: which client IDs, service accounts, partner tenants, or IP ranges may submit.
• Third-party provenance: which third party integrations are approved, with contract/reference to the integration record.

Control test: can an unregistered client submit data successfully? If yes, you have a gap.

Step 3: Define “approved formats” per input surface

Specify what “approved” means in enforceable terms:

• Protocol expectations (HTTP method, required headers, webhook signature requirement)
• Allowed content types (e.g., application/json only)
• Schema requirements (OpenAPI/JSON Schema/Avro/Protobuf schema versions)
• Field-level constraints (length, character set, required/optional fields, numeric ranges)
• File controls (extensions are not enough; define MIME type, magic bytes checks, size limits, encryption requirements, and archive rules)

Document versioning: approved formats must be versioned so you can support change without silent drift.

Step 4: Implement enforcement controls (block or quarantine)

Pick the right enforcement layer for each input type:

APIs / web inputs

• API gateway or WAF rules: block disallowed methods, content types, and oversized payloads.
• Authentication and authorization at the edge: reject unauthenticated requests before they hit app logic.
• Schema validation: enforce request schemas and reject unknown fields if your risk tolerance requires it.

File ingestion

• Restrict drop locations and principals (only approved service accounts can write).
• Validate file type using content inspection and enforce limits.
• Quarantine on failure, with an auditable workflow to review and release.

Queues / events

• Topic-level access controls: only approved publishers.
• Message schema registry enforcement: reject invalid schema versions or unknown fields based on policy.

Step 5: Add an exception process that doesn’t weaken the control

You will have edge cases: emergency data loads, legacy partners, one-off investigations. Manage them explicitly:

• Exception request with business justification, compensating controls, and expiry.
• Approval by the control owner and system owner.
• A plan to migrate the exception back into an approved pathway.

Step 6: Operational monitoring and evidence capture

Minimum operational signals:

• Rejection/quarantine logs with reason codes (untrusted source vs invalid format).
• Alerts on spikes in rejections that may indicate abuse or integration breakage.
• Change records for allowlists and schema changes tied to ticket approvals.

Step 7: Map to owners, procedures, and recurring evidence

Assessors will ask “who runs this” and “how do you prove it works.” Maintain a control mapping that ties SI-10(5) to:

• Named owner(s)
• Procedure/runbook
• Evidence cadence and storage location ¹

If you use Daydream, treat SI-10(5) as a requirement with assigned owners, a standard procedure, and a recurring evidence checklist so collection does not depend on institutional memory ¹.

Required evidence and artifacts to retain

Keep artifacts that prove both design (what you intended) and operation (what actually happens):

Design evidence

• Input Surface Register (current)
• Trusted source allowlists per input surface (clients/service accounts/partner identifiers)
• Approved format definitions (schemas, file rules, interface specs)
• Architecture diagrams showing enforcement points (gateway, ingestion service, quarantine)

Operational evidence

• Configuration exports/screenshots of enforcement rules (gateway policies, bucket ACLs, queue policies)
• Sample logs showing rejections/quarantine with timestamps and reasons
• Test results: negative tests that show invalid inputs are blocked
• Change tickets/approvals for allowlist or schema modifications
• Exceptions register with expiry and closure evidence

Common exam/audit questions and hangups

Expect these themes:

• “Show me all entry points where external data is accepted.” Auditors often find “forgotten” ingestion paths.
• “How do you define ‘trusted source’?” If your answer is informal, you will struggle to defend coverage ¹.
• “Where is the format enforced?” If enforcement only happens deep in application code without consistent tests, reliability becomes a concern.
• “How do you prevent developers from adding new endpoints without controls?” You need a release gate (SDLC checklist, gateway defaults, or platform guardrails).
• “How do you handle third party inputs?” They still need allowlisted identities, signature verification, and schema validation.

Frequent implementation mistakes and how to avoid them

Mistake	Why it fails in audits or incidents	Better pattern
Relying on IP allowlists alone	IPs change; NAT and shared services blur provenance	Bind trust to strong identity (mTLS/OAuth) plus authorization
“We validate in the app” with no consistent policy	Different teams implement differently; easy to bypass	Centralize at gateway/ingestion layer; require schema validation tests
Approved formats described in prose	Not enforceable; drifts over time	Versioned schemas and explicit constraints
Accepting “any JSON”	Attackers can exploit unexpected fields/encodings	Enforce schema, reject unknown fields where appropriate
Exceptions without expiry	Temporary becomes permanent	Time-bound exceptions with compensating controls and closure

Enforcement context and risk implications

Public enforcement cases were not provided in the source catalog for this requirement, so this page does not cite enforcement outcomes.

Risk-wise, SI-10(5) reduces the chance that untrusted integrations, malformed payloads, and uncontrolled file ingestion become a pathway to compromise or data quality failure. It also reduces assessment risk tied to missing implementation evidence, which is a common gap for controls that span many systems ¹.

Practical 30/60/90-day execution plan

Use these phases as an execution sequence; adjust to your environment’s change windows and critical systems.

First 30 days (stabilize scope and ownership)

• Appoint an SI-10(5) control owner and create an Input Surface Register for your highest-risk systems.
• Pick standard definitions for “trusted source” and “approved format” that teams must follow.
• Identify quick wins: enforce authentication at the edge for internet-facing APIs; block unsupported content types.

By 60 days (enforce and prove)

• Implement allowlists for trusted sources on priority input surfaces (API clients, service accounts, partner IDs).
• Publish versioned schemas for priority APIs/events and add schema validation in the gateway or ingestion service.
• Stand up quarantine workflows for file ingestion failures and capture evidence (logs + tickets).

By 90 days (scale and govern)

• Extend the register to remaining systems and require new input surfaces to be reviewed before production.
• Add automated tests (negative cases) to CI/CD for schema and format enforcement.
• Operationalize recurring evidence pulls and exception reviews in Daydream so assessments don’t trigger a scramble ¹.

Frequently Asked Questions

Does SI-10(5) require both “trusted sources” and “approved formats,” or can we implement one?

The text allows “and/or,” so implementations may restrict to trusted sources, approved formats, or both, depending on your defined parameters ¹. In practice, teams usually implement both for high-risk inputs because the risks are different.

What counts as an “information input” for SI-10(5)?

Any data entering a system across a trust boundary counts, including APIs, web forms, uploaded files, message queues, and third-party integrations. Treat internal service-to-service calls as inputs if the caller could be compromised or is managed by a different team.

Are schema validation and input sanitization the same thing?

No. Schema validation checks structure and constraints (types, required fields, length), while sanitization transforms or escapes content. SI-10(5) is primarily about restricting accepted sources and formats, so validation and blocking are central ¹.

How do we handle legacy partners that can’t support modern authentication?

Use a compensating-control approach: restrict network paths, isolate ingestion, require signed payloads if possible, and quarantine failures. Document a time-bound exception with an upgrade plan and clear ownership.

What evidence is most persuasive to an assessor?

A current input surface inventory, enforceable allowlists and schema definitions, and proof of operation (configuration extracts, logs of rejected inputs, and negative test results). Tie each artifact back to a named owner and a repeatable procedure ¹.

Where should enforcement live: WAF, API gateway, or application code?

Put controls as close to the boundary as feasible (gateway/ingestion) so untrusted or malformed inputs are rejected early. Keep application-level validation too, but don’t rely on it as the only enforcement point for SI-10(5).

Footnotes

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

2. NIST SP 800-53 Rev. 5; Source: NIST SP 800-53 Rev. 5 OSCAL JSON