KSI-SVC-PRR—Preventing Residual Risk
Formerly KSI-SVC-08
>Control Description
>NIST 800-53 Controls
>Trust Center Components4
Ways to express your implementation of this indicator — approaches vary by organization size, complexity, and data sensitivity.
From the field: Mature implementations express application security through pipeline-integrated testing — SAST, DAST, and SCA results tracked as dashboard metrics, vulnerability trend lines showing continuous improvement in code quality, and security gates enforced in CI/CD preventing vulnerable code from reaching production.
Application Security Testing Results
AppSec scan results expressing vulnerability trends and fix rates — generated from automated SAST, DAST, and SCA pipelines
Security Development Lifecycle
How security is integrated into the SDLC — threat modeling, code review, and security testing at each phase
AppSec Policy Enforcement
Automated enforcement of application security requirements — security gates blocking builds with critical vulnerabilities
Bug Bounty Program
Bug bounty program as a product security feature — scope, rewards, and responsible disclosure process
>Programmatic Queries
CLI Commands
aws configservice get-compliance-summary-by-config-rule --output tableaws configservice get-compliance-details-by-config-rule --config-rule-name <rule-name> --compliance-types NON_COMPLIANT --query "EvaluationResults[].{Resource:EvaluationResultIdentifier.EvaluationResultQualifier.ResourceId,Time:ResultRecordedTime}" --output table>20x Assessment Focus Areas
Aligned with FedRAMP 20x Phase Two assessment methodology
Completeness & Coverage:
- •Does your residual risk review process cover all change types that could leave unwanted elements — decommissioned services, migrated databases, retired features, and infrastructure teardowns?
- •How do you identify all categories of residual elements — orphaned data, stale credentials, leftover network rules, dangling DNS records, unused storage volumes, and abandoned IAM roles?
- •Are residual risk reviews conducted for inherited and third-party service changes that may affect the confidentiality, integrity, or availability of federal customer data?
- •How do you ensure residual risk reviews cover data remnants in backups, caches, CDN edge nodes, and log archives — not just primary storage?
Automation & Validation:
- •What automated scanning detects orphaned resources, stale configurations, and data remnants after changes are deployed?
- •How do you automatically identify resources that are no longer referenced by any active service but still contain federal customer data?
- •What validation confirms that residual elements have been completely removed — do you verify deletion through post-cleanup scanning?
- •What happens if automated cleanup fails to remove a residual element — how is the failure detected and what manual process applies?
Inventory & Integration:
- •What tools detect orphaned cloud resources (unused EBS volumes, detached network interfaces, stale snapshots, abandoned S3 buckets)?
- •How does your change management process integrate with residual risk review to ensure every significant change triggers a post-change cleanup check?
- •Are residual risk review results tracked in your ticketing system with accountability for remediation?
- •How do you maintain visibility into data remnants across all storage tiers (hot, warm, cold, archive, backup)?
Continuous Evidence & Schedules:
- •How frequently are residual risk reviews conducted, and what evidence demonstrates they occur after every significant change?
- •Is orphaned resource and residual element detection data available via API or dashboard for ongoing monitoring?
- •What evidence shows residual elements identified in the past 90 days were remediated within defined timelines?
- •How do you demonstrate that residual risk to federal customer data is persistently minimized rather than addressed only at assessment time?
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