ゼロトラストアーキテクチャを実装する方法

问题

従来の境界ベースのセキュリティは、攻撃者がネットワーク境界を突破した時点で機能しなくなります。すべてのアクセス要求を個別に検証するゼロトラストアーキテクチャ（ZTA）を実装する必要がありますが、ID、デバイス、ネットワークの検証をどう構成すればよいかがわかりません。

前提条件

• ネットワークセキュリティ境界とその限界の理解
• アイデンティティとアクセス管理（IAM）への習熟
• OAuth 2.0、JWT、mTLS に関する知識

ステップ

1. 1. Define the protect surface and identity pillars

   Identify all assets (data, applications, services) that need protection — this is your protect surface. Map the three Zero Trust pillars: identity (who), device (what), and network (where). Every access decision must evaluate all three. Inventory all users, service accounts, devices, and data flows. Classify data sensitivity levels.

   入力

   assets: database, API, internal admin panel

   输出

   protect_surface: {data, apps, services} | pillars: {identity, device, network}

2. 2. Implement strong identity verification for every request

   Require authentication on every request, not just at session establishment. Use short-lived JWT tokens (5-15 minutes) with frequent refresh. Validate the JWT signature, expiration, issuer, and audience on each request. Implement multi-factor authentication for sensitive operations. Use the JWT parser to inspect token claims and the bearer token generator for service-to-service auth.

   入力

   request with Bearer token

   输出

   verified: identity + claims + expiry

3. 3. Enforce device posture and context-aware policies

   Verify the requesting device is registered, compliant (patched, not compromised), and trusted. Check device certificates via mTLS. Combine identity + device + context (location, time, behavior) into a risk score. Apply least-privilege: grant the minimum permissions needed for the specific action. Use policy engines that evaluate all signals per request, not just at login.

   入力

   user_id + device_id + ip + time

   输出

   risk_score: 0.15 | decision: allow | scope: read:own-data

4. 4. Segment the network and log all traffic

   Replace flat networks with micro-segmentation. Each service communicates only with explicitly allowed peers via encrypted channels (mTLS). Deny all by default, allow by explicit policy. Log every access decision (allow/deny) with full context for audit and anomaly detection. Continuously verify — re-evaluate trust on every request, not just at connection time.

   入力

   service A -> service B

   输出

   policy: allow | logged: {src, dst, action, timestamp}

期待される結果

すべてのアクセス要求が独立して認証され、最小権限で認可され、ログに記録されるゼロトラストアーキテクチャ。ネットワークの場所に基づく暗黙の信頼はありません。

よくあるエラー

Authenticating only at login, trusting the session afterward

Zero Trust requires per-request verification. Use short-lived tokens and validate on every API call, not just at session start.

Trusting internal network traffic by default

Apply the same verification to internal traffic as external. Micro-segmentation ensures no implicit trust between services.

Granting broad roles instead of least privilege

Use attribute-based or policy-based access control. Grant the minimum scope needed per action, not broad admin roles.

トラブルシューティング指引

• If latency increases from per-request verification, cache device posture (not identity) for short periods and use fast local token validation.
• For service-to-service communication, use mTLS with automatic certificate rotation rather than long-lived API keys.
• If policy evaluation becomes complex, use a dedicated policy engine (OPA, Cedar) external to the application code.

セキュリティ上の制限

• Zero Trust reduces but does not eliminate risk — a compromised identity with valid credentials still passes verification.
• All token validation and policy evaluation happen locally; no access decisions are outsourced.
• Continuous logging is essential for detecting anomalous behavior that passes initial verification.