Azure_GRC/base.yaml at main · 4th/Azure_GRC · GitHub

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# ===========================================================
#  Base Policy Defaults — Agentic AI Governance Framework
#  Purpose: Shared defaults all compliance profiles inherit.
#  Usage: Profiles (e.g., nist_rmf-us.yaml) set `extends: ../base.yaml`
#         and may override any `params` or add more `obligations`.
#  Change control: Update via PR; bump `metadata.profile_version`.
# ===========================================================

metadata:
  # A friendly name for this baseline profile
  profile_name: base
  # SemVer for configuration; use to correlate decisions with config version
  profile_version: 1.0.0
  # Who maintains this baseline
  maintainer: "Fourth Industrial Systems (4th)"
  # ISO 8601 date string for last update
  last_updated: "2025-11-09"

params:
  # ---------------- AI Governance defaults -----------------
  # Always disclose AI assistance to end users (set false only for internal tools)
  disclosure_required: true
  # Require manual review for actions classified as high-risk (default false; profiles can enable)
  human_review_required: false
  # Enforcement strictness at runtime: strict | moderate | permissive
  policy_enforcement_level: "strict"
  # Block models that are not on an approved allowlist
  allow_experimental_models: false

  # ---------------- Risk thresholds (defaults) --------------
  # Max acceptable composite risk score (0..1). Profiles can tighten this.
  risk_cap: 0.70
  # Bias score threshold (0..1) beyond which mitigation is required/deny
  bias_threshold: 0.20
  # Minimum explainability score for outputs (0..1)
  explainability_score_min: 0.65

  # ---------------- Operational KPI caps -------------------
  # Daily token usage cap per agent (used for budget/rate-limiting)
  token_cap: 50000
  # Daily operating cost cap in USD (approx; depends on provider rates)
  cost_cap_usd: 10.00
  # Target P95 response time in milliseconds
  latency_target_ms: 2000
  # Expected monthly uptime percentage
  availability_target_pct: 99.5

  # ---------------- Data protection defaults ----------------
  # Whether processing PII/PHI is allowed in this baseline (usually false)
  pii_allowed: false
  # Default retention for transient working data (days)
  data_retention_days: 30
  # Require TLS and storage encryption for any persisted artifacts
  encryption_required: true
  # Retain decision/audit logs at least this many days
  log_retention_days: 90
  # Disallow cross-border transfers unless a profile enables it (e.g., GDPR SCCs)
  cross_border_transfer: false

  # ---------------- Audit / logging defaults ----------------
  # Emit structured allow/deny decisions for SIEM
  enable_decision_logging: true
  # Log output format (json|text); json recommended for SIEM queries
  decision_log_format: "json"
  # Include a trace_id in every decision to correlate with app logs
  include_trace_id: true
  # Require that high-risk actions attach evidence (inputs, checksums, model id)
  evidence_required: true

  # ---------------- Lifecycle management -------------------
  # Days between scheduled (re)training cycles (if applicable)
  retrain_cycle_days: 90
  # Days between model/prompt evaluation checkpoints
  evaluation_interval_days: 30
  # Enable drift detection checks against baselines
  drift_detection_enabled: true

  # ---------------- Regional / legal context ----------------
  # Default jurisdiction label for this baseline (profiles override)
  jurisdiction: "global"
  # Which frameworks this baseline roughly aligns with (informational)
  regulatory_scope: ["NIST AI RMF", "ISO/IEC 42001", "GDPR"]

obligations:
  # Message to present (or log) when disclosure is required
  disclosure_banner: >
    This system uses Agentic AI components governed by policy. Outputs are
    monitored for trustworthiness, fairness, and accountability.
  # Where to route incidents or required approvals
  escalation_contact: "compliance@4th.is"
  # Default target for decision logs (your pipeline can route accordingly)
  audit_log_target: "AzureMonitor"

notes:
  - "All profiles extend this base; do NOT hard-code secrets here."
  - "Parameters are read by the PolicyLoader and can be referenced in rules (e.g., params.risk_cap)."
  - "Keep under version control (Git) and review with change tickets."
  - "Tune thresholds in profile YAMLs (e.g., HIPAA, GDPR, FedRAMP overlays)."