NIST 800-53

The Challenge

Federal agencies and government contractors face strict requirements when deploying AI systems. NIST 800-53 Rev 5 provides the control framework, but applying these controls to autonomous AI agents raises implementation questions:

How do you retain audit records when an AI agent makes dozens of tool calls per conversation?
How do you prove the integrity of audit logs when agents operate at scale?
How do you implement information retention policies across conversations, documents, and logs?

Ragwalla provides the technical controls and evidence artifacts your assessor needs.

AU-11: Audit Record Retention

"Retain audit records for [organization-defined time period] to provide support for after-the-fact investigations of incidents and to meet regulatory and organizational information retention requirements."

What Gets Logged

AI agents generate significantly more audit events than traditional applications. A single agent conversation may produce:

Authentication and session events
Multiple tool call executions
RAG document retrievals
External API invocations
Response generation events

Ragwalla captures all agent activity in a tamper-evident audit chain.

Tamper-Evident Integrity

Each audit entry is cryptographically chained to the previous entry. This chain structure enables detection of:

Deleted entries — Gap in the sequence
Modified entries — Integrity check failure
Inserted entries — Chain break at insertion point

Your assessor can verify the chain has not been tampered with.

Configurable Retention

Set audit log retention per organization:

Retention Period	Use Case
1 year	Standard business operations
7 years	Financial services, healthcare
Indefinite	When required by policy

Archive Preservation

When audit logs reach retention limits, Ragwalla preserves chain integrity by archiving records before deletion. This ensures you can demonstrate unbroken chain-of-custody even after retention cleanup.

SI-12: Information Management and Retention

"Manage and retain information within the system and information output from the system in accordance with applicable laws, Executive Orders, directives, regulations, policies, standards, guidelines and operational requirements."

Multi-Category Retention

AI agents create and process multiple categories of information, each with independent retention controls:

Category	Examples	Control
Conversation data	User messages, agent responses	Chat retention setting
Audit records	Tool calls, access events	Log retention setting
Knowledge base	RAG documents, embeddings	File retention setting

Hierarchical Policies

Set organization-wide defaults with project-specific overrides:

Organization: Federal Agency XYZ
├── Default: 7-year retention for logs and files
├── Project: Public Inquiry Bot
│   └── 90-day chat retention (PII minimization)
└── Project: Internal HR Assistant
    └── 7-year chat retention (personnel records)

Legal Hold for Preservation

When NARA schedules, litigation, or FOIA requests require preservation beyond normal retention:

Hold Type	Federal Context
Litigation	Litigation hold per FRCP
Regulatory investigation	OIG, GAO, or agency investigation
FOIA request	5 U.S.C. § 552 response
Internal investigation	Administrative inquiry

Protected data is excluded from automated retention until the hold is released.

Evidence for Assessors

AU-11 Assessment

Your assessor can verify:

Policy exists — Retention periods defined per organization
Retention enforced — Job execution history shows policy running
Chain integrity — Cryptographic verification of audit logs
Archive preservation — Expired records retained in archive

SI-12 Assessment