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reopt Handbook
reopt Handbook
AI Security and Compliance Operations

Strategy and Governance

Risk GovernanceData ProtectionSecure Architecture

Security Controls

Prompt Injection DefenseAccess Control and SecretsAudit Readiness

Operations and Leadership

Incident ResponseBoard Reporting

Appendix

GlossaryVerificationUpdates
Handbook›AI Security and Compliance›Access Control and Secrets
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Access Control and Secrets

Separate human, service, connector, and agent permissions, then connect least privilege, secret rotation, approval gates, and audit evidence.

Written and reviewed by Eric Han · Co-founder & CTO, reopt

Key takeaways

  • Separate human, service, connector, and agent permissions, then connect least privilege, secret rotation, approval gates, and audit evidence.
  • Use this chapter as a first-pass operating checklist before changing systems, data, permissions, or customer-facing workflows.
  • Validate platform-specific details against current official docs or internal policy before rollout.

MCP boundaries: token audience and OAuth URLs

Current MCP security guidance forbids accepting tokens not issued for the server and passing them unchanged to downstream APIs. Validate the intended resource/audience and resolve downstream credentials separately. MCP proxies need per-client consent and exact registered redirect URI matching for third-party OAuth flows.

Server-side clients fetching OAuth metadata should enforce HTTPS and address policy on the initial URL and every redirect. Restrict private, loopback, link-local, and cloud metadata access according to the environment; test DNS and IPv6 bypasses. Avoid hand-written prefix checks. Explicitly design exceptions for private enterprise MCP endpoints.

Regression caseExpected result
Valid token for another resourceAuthentication rejected
Tenant A approval used for tenant B accessExecution-time authorization rejected
Permission revoked while approval is pendingRecheck and reject before dispatch
Public OAuth URL redirects internallyNetwork policy rejects before fetching

MCP security best practices.

AI systems introduce a new permission actor: the agent. It may read, decide, and trigger tools on behalf of a user or workflow, so access control must be explicit.

Identity Types

IdentityControl need
Human userRole, tenant, consent, session
Service accountScoped API access and rotation
Agent runtimeTask-scoped permissions and audit
Tool connectorLeast privilege and data filtering
AdministratorBreak-glass policy and monitoring

Secret Rules

  • Store secrets in approved secret managers or platform environment variables.
  • Never put secrets in prompts, memories, documentation examples, or logs.
  • Rotate keys with no expiration or unclear owner.
  • Separate development, staging, and production credentials.
  • Monitor privileged token usage and failed access attempts.

Approval Gate

Any AI-initiated action that changes money, customer records, permissions, legal status, or production state should require explicit policy and human review.

Related docs

Security Governance

Enterprise Project Architecture · Manage secrets, access, dependencies, permissions, and approval rules in enterprise projects.

MCP Integration

Advanced Codex Usage · Connect Codex to MCP servers with explicit tool, data, and trust boundaries.

Ch7. Tools, Approval, Connections

Enterprise Eve Agent Development · Design Eve authored tools, human approval, MCP/OpenAPI connections, and OAuth boundaries as enterprise security surfaces.

Secure Architecture

Design AI systems with policy boundaries, isolation, logging, and safe tool access.

MCP Enterprise Data

Vercel Enterprise AI Platform · Connect enterprise systems to AI agents through MCP tools, resources, and prompts.

Prompt Injection Defense

Defend AI systems against malicious instructions in user input, retrieved content, and tool output.

Audit Readiness

Build evidence pipelines for AI controls before formal audits begin.

On this page

MCP boundaries: token audience and OAuth URLsIdentity TypesSecret RulesApproval Gate