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APRF-10

Authentication

Strong identity for users, services, agents, and MCP callers.

Purpose

Ensure every actor that can invoke AI capabilities—humans, services, agents, MCP clients—is authenticated with appropriate assurance.

Engineering philosophy

AI endpoints are privileged application surfaces. Anonymous or shared credentials for agents and MCP are incompatible with production readiness beyond Level 1.

Why it matters

Unauthenticated model and tool endpoints become public compute and data exfiltration oracles. Agent impersonation enables privilege abuse across systems.

Common failures

  • Public API keys embedded in clients calling powerful agents
  • MCP servers listening without auth
  • Service accounts shared across many agents
  • No MFA for admin consoles controlling prompts and tools

Mandatory checks

Gate controls. Each check is pass/fail via artifact + pass condition. Expected from the annotated capability level when the system meets the minimum criticality tier.

  • AUTHN-M1L3 · DefinedTier 2 · Productionautomated

    Customer-facing AI APIs shall reject unauthenticated callers

    Artifact
    Automated auth probe report covering all production AI HTTP/RPC routes
    Pass condition
    100% of probed production AI endpoints return 401/403 without valid credentials; probe inventory matches production route catalog
  • AUTHN-M2L3 · DefinedTier 2 · Productionhybrid

    Service-to-service and MCP connections shall use strong machine identity

    Artifact
    MCP/S2S connection inventory + auth config export
    Pass condition
    0 production MCP or AI S2S connections accept anonymous access or shared long-lived static keys; each connection has a named machine identity
  • AUTHN-M3L3 · DefinedTier 2 · Productionhybrid

    Administrative access to AI control planes shall require strong authentication including MFA

    Artifact
    IdP policy export for AI admin roles + break-glass account inventory
    Pass condition
    100% of AI control-plane admin roles enforce MFA; break-glass accounts ≤ documented maximum and have monitoring enabled
  • AUTHN-M4L5 · OptimizingTier 3 · Mission Criticalhybrid

    End-user identity shall remain bound through agent and tool chains

    Artifact
    Identity-propagation design + sample traces showing end-user subject on tool calls
    Pass condition
    PASS if 100% of sampled privileged tool calls in the latest review carry an end-user (or documented service) subject; 0 anonymous privileged hops

Evidence required

  • Auth architecture for AI and MCP surfaces
  • Evidence that anonymous access is disabled in production
  • Admin access controls documentation

Severity & risk

Severity
critical
Impact if violated
Risk level
critical
Typical residual risk (impact × likelihood)

Engineering best practices

  • Prefer OAuth2/OIDC or workload identity over static API keys
  • Issue distinct identities per agent class
  • Rotate credentials automatically; detect leaked keys in repos and prompts
  • Authenticate both directions for A2A where feasible

Automatic validations

  • Integration tests rejecting unauthenticated calls
  • Secret scanning for exposed AI API keys
  • Config checks that MCP auth is enabled

Manual validations

  • Identity design review for new agent entry points
  • Periodic access review of AI admin roles

Examples

  • An MCP server requires OAuth for every client; local-dev uses a distinct non-prod issuer
  • A voice AI channel authenticates the telephony session before invoking tools

References

Crosswalks

  • Secure & Resilient Secure and Resilient

    NIST AI Risk Management Framework · aligns-with

  • CC6 Logical and Physical Access

    SOC 2 Trust Services Criteria · evidence-for

  • Security Security

    AWS Well-Architected Framework · aligns-with

Future evolution

Standard agent identity profiles and passport-like credentials for cross-org A2A.