SC-30(2): Randomness

SC-30(2): Randomness requires you to deliberately introduce randomness into selected operations and assets so attackers cannot reliably predict system behavior. To operationalize it, define where randomness is needed (e.g., crypto, session values, scheduling, allocation), standardize approved randomness sources, implement them in systems, and keep evidence that randomness is designed, configured, and periodically verified. ¹

Key takeaways:

• Scope the “randomness” requirement to concrete use cases (cryptography, tokens, timing, allocation, defenses) and assign owners per use case.
• Standardize approved entropy sources and libraries, then block ad hoc or weak pseudo-random approaches in engineering practice.
• Retain configuration and test evidence that randomness is implemented and operating as intended, not just documented.

Compliance teams often treat “randomness” as a cryptography-only topic. SC-30(2) is broader: it expects you to add unpredictability where predictability creates attack paths. That can include how secrets are generated, how sessions are protected, how jobs are scheduled, how identifiers are created, and how security controls behave under attack. The practical goal is simple: reduce the attacker’s ability to plan, replay, or systematically probe your environment.

The control text is intentionally parameterized in NIST language, which creates an execution gap: engineers ask “randomness where?” and auditors ask “show me it’s real, not a policy.” This page closes that gap with requirement-level implementation guidance you can hand to a control owner. You’ll get a scoping method, an implementation checklist, and an evidence pack that maps cleanly to assessment conversations.

If you run federal information systems or contractor systems handling federal data, SC-30(2) belongs in your baseline control set and your SDLC guardrails. ²

What SC-30(2) requires (plain English)

SC-30(2): randomness requirement means you must intentionally add unpredictability to chosen systems, processes, or assets so an adversary cannot easily guess values or system behavior. Your implementation must be repeatable (standard methods, approved components) and verifiable (tests, configs, code, and operational proof).

A useful operator translation:

• Identify predictable behaviors that create security risk (guessable tokens, deterministic scheduling, repeatable allocation, predictable defenses).
• Add randomness in those places using approved randomness sources (strong entropy sources, approved crypto libraries, controlled mechanisms).
• Prove it’s implemented and stays implemented through configuration management, code review controls, and periodic verification.

This control is an enhancement under the System and Communications Protection family and is commonly assessed alongside cryptographic and secure engineering expectations. ²

Regulatory text

“Employ {{ insert: param, sc-30.02_odp }} to introduce randomness into organizational operations and assets.” ¹

What the operator must do with this text

NIST leaves the specific “organizationally defined parameters” (ODPs) to you. Operationally, you need to:

1. Define the parameter: the concrete techniques/places you will apply randomness (your sc-30.02_odp).
2. Implement it: deploy technical and procedural mechanisms that generate or apply randomness.
3. Institutionalize it: make it part of build standards, configuration baselines, and verification so it does not regress.

Auditors will focus less on your prose definition and more on whether your definition is reflected in engineering reality.

Who it applies to (entity and operational context)

Entity types

• Federal information systems
• Contractor systems handling federal data ²

Operational contexts where SC-30(2) shows up

• Identity and access systems (session IDs, reset tokens, API keys, nonces)
• Cryptographic operations (key generation, IVs, salts, signature nonces)
• Platform controls (ASLR, randomized ports/ephemeral ports, randomized backoff/jitter)
• Workload and job scheduling (randomized schedule offsets to reduce predictability and collision)
• Data and resource allocation (random identifiers, randomized shard placement where appropriate)
• Security defenses (rate limiting jitter, randomized challenge behavior)

You do not need to “randomize everything.” You need to randomize the right things, document the choice, and demonstrate consistent operation.

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

Step 1: Assign a control owner and define “randomness scope”

Pick a primary owner (usually Security Engineering or Platform Security) and name contributing owners for app engineering and infrastructure.

Create a one-page “SC-30(2) Randomness Scope” that answers:

• Which assets and operations require randomness (by system type).
• Which mechanisms are approved (libraries, platform features, entropy sources).
• Where randomness is prohibited or constrained (e.g., deterministic testing paths, reproducible builds, regulated workflows), with compensating controls.

This is where many programs fail: they never convert the ODP placeholder into an implementable scope statement. ¹

Step 2: Standardize approved randomness sources and patterns

Define engineering-approved patterns, for example:

• Approved cryptographic libraries and their RNG interfaces.
• Approved entropy sources (OS-provided CSPRNG) and rules against custom PRNGs for security-sensitive uses.
• Rules for tokens/IDs (length, character set, rotation expectations) as internal standards. Keep this as engineering guidance, not “security by vibes.”

Make it hard to do the wrong thing:

• Add secure coding guidelines covering randomness.
• Add code review checks or linters to flag non-cryptographic PRNG in security-sensitive contexts.
• Provide vetted helper functions so teams don’t re-implement token generation.

Step 3: Implement randomness in your highest-risk use cases first

Prioritize where predictability becomes compromise:

A. Secrets and tokens

• Ensure session IDs, password reset links, API tokens, CSRF tokens, and one-time codes come from approved secure generators.
• Ensure uniqueness and non-guessability requirements are captured in engineering requirements.

B. Cryptographic material

• Confirm keys, IVs, salts, and nonces are generated using approved secure methods.
• Verify hardware-backed generation where applicable to your architecture.

C. Operational timing and behavior

• Add jitter to retry logic to reduce coordinated retry storms and predictability.
• Randomize schedule start offsets for recurring jobs where predictability creates operational or security risk.

Document exceptions. Some systems need determinism for reproducibility; treat those as risk decisions with compensating controls.

Step 4: Bake it into SDLC and change management

Make SC-30(2) “sticky”:

• Add a design review checklist item: “Does this feature generate any secrets/tokens/IDs? If yes, show randomness source and tests.”
• Add a threat modeling prompt: “What could an attacker predict here?”
• Require security sign-off for any change to randomness-related libraries, entropy sources, or token formats.

Step 5: Verify and monitor

Verification needs to be practical:

• Configuration verification (platform settings that enable randomization features).
• Code-level verification (approved RNG calls; no fallback to weak generators).
• Operational checks (spot checks of token generation paths; review of incident tickets tied to predictability issues).

Avoid overpromising with “statistical randomness tests” unless you actually have the expertise and scope; auditors usually want evidence of correct controls and correct sources, not academic test suites.

Required evidence and artifacts to retain

Use an evidence pack that an assessor can consume quickly:

Governance artifacts

• SC-30(2) scope statement (ODP definition): what you randomize, where, and how. ¹
• Control ownership and RACI for randomness use cases.
• Secure coding standard section on randomness (approved RNGs, banned PRNGs for security).

Technical artifacts

• Architecture/design docs showing token/secret generation flows.
• Code references (repo paths, pull requests) demonstrating approved RNG usage in critical paths.
• Configuration baselines for platform randomization features (as applicable).
• Change records for updates to crypto libraries and randomness-related modules.

Operating evidence

• SDLC checklists completed for relevant releases.
• Periodic verification results (e.g., internal review notes, scans, or manual attestations by service owners).
• Exceptions register documenting deterministic requirements and compensating controls.

A common gap is having policy text but no linkage to the actual services that generate tokens or keys. Map evidence to systems.

Common exam/audit questions and hangups

Expect these:

1. “Define your sc-30.02_odp parameter.”
   Have your one-page scope statement ready. ¹

2. “Where specifically did you introduce randomness?”
   Provide a system list and the specific control points (tokens, nonces, jitter, scheduling).

3. “How do you know developers aren’t using weak PRNGs?”
   Show coding standards, code review gates, and sample PRs.

4. “How do you maintain this over time?”
   Point to SDLC integration, dependency management controls, and periodic verification.

5. “Show me evidence for System X.”
   Be prepared with a per-system evidence snippet: design doc + code pointer + config baseline.

Frequent implementation mistakes (and how to avoid them)

Mistake	Why it fails	Fix
Treating SC-30(2) as “crypto team’s job” only	Predictability exists outside cryptography	Scope multiple use cases (tokens, timing, scheduling, defense behaviors)
Writing a policy but leaving the ODP undefined	Assessors can’t test an undefined requirement	Publish the sc-30.02_odp scope statement and tie it to systems 1
Allowing ad hoc token generation helpers	Inconsistent strength, hard to audit	Provide approved shared libraries and block weak generators in review
No evidence trail from control to systems	“Implemented” becomes unprovable	Maintain a system mapping with artifacts per system
Exceptions handled informally	Determinism creeps into sensitive paths	Track exceptions with owner sign-off and compensating controls

Enforcement context and risk implications

No public enforcement cases were provided in the source material for this requirement, so treat SC-30(2) as an assessment and authorization readiness control rather than a control with direct published penalty examples in this dataset. The real risk is technical: predictable tokens, IDs, and behaviors enable guessing attacks, replay, and systematic probing. Your compliance risk follows quickly: inability to show defined parameters and operating evidence creates assessment findings. ¹

Practical 30/60/90-day execution plan

First 30 days (Immediate stabilization)

• Name the control owner and publish the SC-30(2) scope statement (your sc-30.02_odp definition). ¹
• Inventory systems that generate secrets/tokens/keys and rank them by exposure.
• Publish approved RNG sources/libraries and a “do not use” list for security-sensitive contexts.
• Start an exceptions register for deterministic needs.

Next 60 days (Implementation and guardrails)

• Update SDLC checklists and threat model prompts to include randomness decisions.
• Implement shared libraries/helpers for token and identifier generation where gaps exist.
• Add code review rules or static checks for weak randomness patterns in sensitive modules.
• Collect evidence for your top systems: design doc + code pointers + config baselines.

By 90 days (Assessment-ready evidence and monitoring)

• Complete coverage for remaining in-scope systems, or document phased exceptions with dates and owners.
• Run a lightweight verification cycle and retain results (spot checks, review notes, scan outputs).
• Package the evidence by system for assessors: one folder per system with a consistent index.

Daydream can help you keep this control “alive” by mapping SC-30(2) to a clear owner, procedure, and recurring evidence list, so audits do not become a scavenger hunt. ¹

Frequently Asked Questions

Does SC-30(2) only apply to cryptographic key generation?

No. The text applies to “organizational operations and assets,” so scope should include any predictable behavior that creates attack paths, including tokens, identifiers, timing, and defense behaviors. ¹

What does the placeholder “sc-30.02_odp” mean in practice?

It means you must define your organization’s parameter for where and how you introduce randomness. Assessors expect a documented scope and proof the scope matches implementation. ¹

How do we prove compliance without running statistical randomness tests?

Most teams show evidence of approved entropy sources and correct implementation: architecture docs, code references to approved RNG calls, and configuration baselines. Add periodic verification that focuses on preventing regressions.

Our system needs deterministic behavior for testing or reproducible builds. Are we noncompliant?

Not automatically. Document an exception, restrict determinism to non-production paths where possible, and add compensating controls so security-sensitive values remain unpredictable.

What’s the fastest way to reduce audit risk for SC-30(2)?

Define the scope (ODP) and map it to specific systems with owner-assigned evidence artifacts. The most common finding is “no implementation evidence,” not a nuanced critique of your randomness model. ¹

How should a GRC team coordinate with engineering on this?

GRC should own the requirement definition, evidence expectations, and assessment mapping, while engineering owns implementation and technical verification. A shared system-by-system evidence index prevents gaps during audits.

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