Project 12: Policy, Safety, and Security Compliance Gate

Build an enforceable control plane that keeps app behavior policy-safe under real misuse pressure.

Quick Reference

Attribute	Value
Difficulty	Advanced
Time Estimate	1-2 weeks
Main Programming Language	TypeScript
Alternative Programming Languages	Python, Go
Coolness Level	Level 4
Business Potential	High for enterprise adoption
Prerequisites	Tool schema experience, auth basics
Key Topics	Policy matrix, authorization checks, redaction and retention

1. Learning Objectives

1. Encode policy controls as executable checks.
2. Enforce deny-by-default logic for mutating operations.
3. Validate security and privacy controls with evidence.
4. Detect and prevent policy drift after updates.

2. All Theory Needed (Per-Concept Breakdown)

Compliance-as-Code for ChatGPT Apps

Fundamentals Compliance is behavior, not paperwork. You need controls at planner, schema, execution, and output boundaries. Every policy claim must map to technical enforcement.

Deep Dive into the concept Start with a control taxonomy: intent controls, input controls, authorization controls, output controls, and retention controls. Intent controls constrain what tasks tools are meant to do. Input controls constrain argument shape and avoid dangerous ambiguity. Authorization controls verify scopes and tenant context server-side. Output controls prevent sensitive leakage in content and logs. Retention controls ensure stored data matches documented policy windows.

Use a policy matrix per tool. Include allowed/denied intents, required confirmations, required scopes, risk level, log class, and remediation behavior. For each rule, add at least one automated test. Run this suite on every release candidate.

Drift prevention is critical. Whenever metadata, tool description, or scope changes, rerun adversarial prompts and compare expected denies. Treat unexpected allows as critical failures.

Minimal concrete example

tool=delete_invoice
risk=high
required_scope=invoices.write
requires_confirm=true
blocked_intents=["bulk delete", "silent deletion"]
on_violation=POLICY_DENIED

3. Project Specification

3.1 What You Will Build

A policy gate that validates safe behavior, secure authz enforcement, and compliant data handling before release.

3.2 Functional Requirements

1. Define tool-level policy matrix.
2. Implement policy-denied and auth-denied error classes.
3. Add log redaction and retention checks.
4. Add adversarial prompt regression tests.

3.3 Real World Outcome

$ npm run policy:verify
[ok] blocked intents denied
[ok] confirmation required for high-risk writes
[ok] scope checks server-side
[ok] no secret/token leaks in logs
[ok] retention policy checks
critical_findings=0

4. Solution Architecture

Prompt Intent -> Schema Gate -> Auth/Policy Gate -> Execution -> Sanitized Output + Audit

5. Implementation Guide

5.1 The Core Question You’re Answering

“How do we prove this app cannot perform unsafe actions even when prompted to?”

5.2 Concepts You Must Understand First

1. Deny-by-default design.
2. Authorization vs authentication.
3. Data minimization and log hygiene.

5.3 Questions to Guide Your Design

1. Which tools need highest scrutiny?
2. Which policy checks are blocking at release time?
3. How is policy drift detected and owned?

5.4 Thinking Exercise

Model failure handling for an unauthorized write request across planner text, tool errors, and UI messaging.

5.5 The Interview Questions They’ll Ask

1. How do you map policy to executable tests?
2. What prevents scope bypasses?
3. How do you test for data leakage?
4. What signals policy drift fastest?
5. How do you respond to violations in production?

5.6 Hints in Layers

• Hint 1: Build policy matrix before coding checks.
• Hint 2: Normalize deny errors first.
• Hint 3: Add replayable adversarial prompt suites.
• Hint 4: Treat any unexpected allow as release-blocking.

5.7 Books That Will Help

Topic	Book	Chapter
Security governance	“Foundations of Information Security”	Governance chapters
Boundaries	“Clean Architecture”	Policy boundaries
Defensive quality	“Code Complete”	Robustness/testing

6. Testing Strategy

• Blocked-intent prompt tests.
• Scope mismatch and revoked-token tests.
• Secret redaction checks in logs and traces.

7. Common Pitfalls & Debugging

Pitfall	Symptom	Solution
Client-side-only authz	Endpoint abuse	Enforce checks server-side
Generic deny errors	User confusion	Return deterministic and actionable errors
No drift tests	Silent policy regressions	Run adversarial suites every release

8. Extensions & Challenges

• Add severity scoring for policy violations.
• Add weekly drift report automation.
• Add cross-team policy ownership workflow.

9. Real-World Connections

• Enterprise trust and safety programs
• Compliance audits for AI products
• Security operations for internal copilots

10. Resources

• OpenAI Apps SDK: Security & privacy
• OpenAI Usage Policies
• OpenAI Terms for Connectors and Actions

11. Self-Assessment Checklist

• I can describe tool-level policy controls clearly.
• I can prove server-side authorization is enforced.
• I can detect and remediate policy drift.

12. Submission / Completion Criteria

Minimum Viable Completion

• Working policy matrix with core deny/allow tests.

Full Completion

• Includes adversarial prompt regressions, log redaction checks, and release-blocking drift detection.