secure-ai-engineering-framework

A data-boundary framework for using frontier AI and local models in high-security software engineering.

The operating philosophy is simple:

• Use GPT-5.5 for fast, strong code creation when the context is code or sanitized engineering material.
• Use GPT-5.5 Pro for hard coding, security-sensitive architecture, and difficult debugging when the context is external-safe.
• Use the latest Claude Opus policy entry as an independent second reviewer.
• Use a local model for production data, government data, user records, private logs, documents, screenshots, and any data interaction.
• Use a private repo/document index that sends only the context needed for the task.
• Use secure-code-skill-cascade for generated code and review.

The boundary is the product: code can move to frontier models after classification and minimization; sensitive data cannot.

flowchart TD
  A["Engineering task"] --> B["Classify context"]
  B --> C{"Context class?"}
  C -->|Code + sanitized context| D["GPT-5.5 / GPT-5.5 Pro coding"]
  C -->|Generated patch| E["Claude Opus second review"]
  C -->|Production, government, user data| F["Local private model"]
  C -->|Secrets| G["Stop + rotate"]
  F --> H["Synthetic mocks / safe summaries"]
  H --> D
  D --> I["secure-code-skill-cascade"]
  E --> I
  I --> J["Tests + audit evidence + residual risk"]

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Quick Start

npm install
npm test
node scripts/classify.mjs --text "export function add(a,b){return a+b}"
node scripts/mock-from-schema.mjs --schema examples/schema/customer-case.schema.json
node scripts/context-pack.mjs --manifest examples/context-manifest.json
node scripts/compose.mjs --scenario production-db-debug

What Is Included

• skills/secure-ai-engineering/SKILL.md: root skill for high-security AI engineering.
• skills/secure-ai-engineering/references/: focused policy and workflow modules.
• portable/secure-ai-engineering-framework.md: portable prompt bundle.
• secure-ai-engineering.config.json: model roles, data classes, routes, and controls.
• scripts/classify.mjs: lightweight prompt/context classifier.
• scripts/mock-from-schema.mjs: deterministic synthetic mock generator.
• scripts/context-pack.mjs: minimal context pack builder with classification checks.
• scripts/compose.mjs: scenario-specific skill composer.
• examples/scenarios/: high-security workflow scenarios.
• examples/boundary-demos/: before/after examples for boundary failures and safe alternatives.

Data Classes

Class	Route
PUBLIC_CODE	External frontier model allowed.
PRIVATE_REPO_CONTEXT	External frontier model allowed after minimization and classification.
SENSITIVE_DATA	Local model only, then synthetic mock or safe summary.
SECRETS	Block; do not send to any model; rotate if exposed.

Model Roles

Role	Default
Primary coding	GPT-5.5
Hard coding	GPT-5.5 Pro
Second review	Latest Claude Opus policy entry
Sensitive data interaction	Local private model

The model names are policy defaults, not hard-coded API requirements. If a provider changes naming or availability, preserve the role: frontier coder, independent reviewer, or local-private model.

Module Map

Module	Use When
data-boundary-policy	Classifying context and deciding whether it can cross the external AI boundary.
model-routing	Choosing GPT-5.5, GPT-5.5 Pro, Claude Opus, or a local model.
frontier-coding-workflow	Building external-safe coding prompts from source and sanitized context.
second-reviewer-workflow	Independent Claude Opus review of generated code and risks.
local-private-data-workflow	Production data, government records, private logs, documents, and screenshots.
private-context-index	Minimal private repo/document context packs.
synthetic-mock-generation	Schema-shaped mocks for external debugging without real data.
secure-code-integration	Integration with Mirogate secure-code-skill-cascade.
audit-evidence	Route decisions, context classes, review evidence, tests, and residual risks.
government-procurement-controls	Public-sector/high-security delivery controls.
incident-stop-rules	Stop, contain, rotate, and restart safely after boundary violations.

Example Scenarios

node scripts/compose.mjs --scenario hard-code-feature
node scripts/compose.mjs --scenario second-review
node scripts/compose.mjs --scenario production-db-debug
node scripts/compose.mjs --scenario government-document-analysis
node scripts/compose.mjs --scenario private-context-pack
node scripts/compose.mjs --scenario incident-hotfix

Limits

This is not a compliance certification, legal opinion, classified-system approval, or guarantee that a workflow is safe for every government or regulated environment. It is a practical engineering framework for keeping AI-assisted development fast while enforcing a hard data boundary.

Primary references:

• OpenAI latest model guidance: https://developers.openai.com/api/docs/guides/latest-model.md
• Anthropic model overview: https://docs.anthropic.com/en/docs/about-claude/models/overview
• NIST AI Risk Management Framework: https://www.nist.gov/itl/ai-risk-management-framework
• NIST Generative AI Profile: https://www.nist.gov/publications/artificial-intelligence-risk-management-framework-generative-artificial-intelligence-profile
• OWASP Top 10 for LLM Applications: https://genai.owasp.org/llm-top-10/
• Mirogate secure-code-skill-cascade: https://mirogate.com/open-source/secure-code-skill-cascade/

Security

Please report security issues to security@mirogate.com. See SECURITY.md.