How to build an ATO Package Generator
This agent automates the end-to-end process of collecting, mapping, validating, and packaging all required documentation and evidence for DoD RMF/ATO (IATT-C) compliance.
Challenge
Manual RMF/ATO documentation and evidence mapping is slow, error-prone, and requires deep expertise in compliance frameworks.
Industry
Government
Industrials
Department
Compliance
Content Creation
Integrations
OpenAI
Google Drive
Workflow Overview
1. User Inputs & Evidence Collection
System Information and Categorization Input (
in-0):The user provides key system details (name, ID, description, owner) and categorization info (CIA assessment, impact level, PII/PHI overlays).
System Boundary, Environment Types, External Systems, and Roles (
in-1):The user supplies information about system boundaries, required environments, external interfacing systems, and roles.
Evidence Upload (
doc-0):The user uploads supporting evidence/artifacts (e.g., diagrams, design docs, inventories).
2. System Context Synthesis
System Context Collector (
llm-0):Purpose: Synthesizes all user/system input and uploaded files into a structured context object.
How: Merges the above inputs and evidence to extract system metadata, mission objectives, boundaries, data flows, trust boundaries, CIA ratings, information types, and hardware/software inventories.
Special Logic: If inventories are missing, it flags the gap explicitly.
3. Control Selection
Control Selector (
llm-1):Purpose: Selects and tailors the full set of applicable NIST 800-53 Rev. 5 controls for the system.
How: Uses the synthesized system context to determine which controls apply, including overlays and parameterization. Decides applicability, implementation status, enhancements, and inheritance for each control.
4. Evidence Mapping
Evidence Aggregator (
llm-2):Purpose: Maps uploaded evidence to the selected controls.
How: Ensures every control has at least one evidence item (or a placeholder if missing), and extracts metadata and assessment procedures for each artifact.
5. Documentation Drafting
Documentation Drafter (
llm-3):Purpose: Drafts the full ATO documentation package (SSP, SAP, SAR, POA&M, eMASS export).
How: Uses the system context, controls, and evidence repository to generate each section of the package.
6. Compliance Validation
Compliance Validator (
llm-4):Purpose: Validates evidence and control implementation, flags gaps, and produces a validation report for POA&M generation.
How: Checks each control against the provided evidence, flags any gaps, computes residual risk, and generates SAP/SAR stubs for failed controls.
7. Review & POA&M Generation
Reviewer & POA&M Generator (
llm-5):Purpose: Performs QA/QC, generates the final POA&M, and packages the final ATO submission.
How: Reviews the validated package and validation report, generates a POA&M for controls with missing/insufficient evidence, and packages the final ATO submission.
8. Formatting & Output
Formatter (
llm-6):Purpose: Formats the output of the Reviewer LLM into a legible, professional report.
How: Takes the final package and POA&M, and produces a well-structured narrative report for submission.
ATO Package Output (
out-0):Purpose: Outputs the final, formatted ATO package.
POA&M Output (
out-1):Purpose: Outputs the POA&M report.
Key Points
Inputs: The process starts with user/system information and evidence uploads.
LLM Chain: Each LLM node builds on the previous, adding structure, selecting controls, mapping evidence, drafting documents, validating compliance, and generating the final package.
Outputs: The flow produces both a formatted ATO package and a POA&M report, ready for submission.





