TINLANCE / SECURITY ENGINEERING

Security is a control path, not a checklist.

Tinlance treats identity, tenant context, authorization, policy, risk, approval, execution, output controls and audit evidence as part of the AI engineering path.

Server-side authorization Fail-closed security boundaries Evidence-aware verification

01 / SECURITY ARCHITECTURE

Identity → policy → controlled action.

Model output, memory, tool output and external inputs are treated as untrusted. Authorization remains a server-side decision.

CONTROL PATH

Identity → Tenant → Principal → Permission → Policy → Risk → Approval → Execution → Output → Audit

This is the control sequence documented for the M7 security gateway. M9 executes within it; M6 remains the MCP/tool boundary; M8 remains the evaluation authority.

M7Security control plane
M6MCP / tool boundary
M8Evaluation authority

02 / ENGINEERING CONTROLS

CONTROL

Identity & access

Better Auth provides the application identity boundary. Organization membership, roles and permissions are enforced server-side rather than by UI state.

CONTROL

Tenant isolation

Customer-owned resources are scoped to an organization boundary. The platform uses tenant-aware authorization and PostgreSQL persistence as a backstop.

CONTROL

Policy & risk

M7 provides a deterministic authorization and risk boundary around sensitive AI actions, with fail-closed behavior and explicit approval or step-up requirements.

CONTROL

Agent execution

M9 keeps identity-bound agent execution bounded. Agent capabilities, memory, cancellation, approvals and runtime evidence remain controlled rather than implicit model authority.

CONTROL

MCP & tools

M6 is the MCP/tool boundary. Tool use is mediated by authorization and policy rather than exposing unrestricted model-to-system access.

CONTROL

Evaluation

M8 provides evaluation and regression controls for AI behavior. Evaluation is an assurance mechanism, not a claim that an AI system is universally safe or accurate.

03 / VERIFICATION

Evidence has a status.

Security language distinguishes implementation, testing, external validation and assurance. A green CI run is not customer production evidence.

Status: ImplementedStatus: Tested

Current controls

Identity, tenant authorization, M6/M7/M8/M9 boundaries and audit-oriented controls are represented in the current repository.

Status: Tested

Repository verification

Type checking, linting, tests, builds, dependency audits, SAST, secret scanning, container validation and SBOM validation as configured by CI.

A green CI run demonstrates repository checks for the tested revision; it is not customer-specific production validation.

Status: Planned

External assurance

Certification, regulatory approval, customer deployment and independent security assurance are not inferred from repository controls.

TECHNICAL ASSESSMENT

Bring your AI system into the control path.

Use a technical assessment to examine architecture, data boundaries, tool access, security controls and delivery constraints in your environment.

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