AI 구축 및 실행을 위한 정책 패턴

[service.ml-training]
[policy]
# Pipelines read only consented data from their own region
grant role training-pipeline read expr:^/datasets/ if consent == true && data_region == job_region
# Restricted datasets never enter training
deny role training-pipeline read expr:^/datasets/restricted/
grant role ml-engineer start /jobs/training if gpu_hours <= 64
grant role ml-engineer export expr:^/checkpoints/
[rolepolicy]
grant entity pipeline-churn training-pipeline
grant group ml-team ml-engineer

데이터셋별 동의 및 리전 확인, 제한된 데이터에 대한 직접 거부, 작업 시작 시 GPU 시간 제한 적용.

[service.model-registry]
[policy]
grant role ml-engineer register expr:^/models/
grant role release-manager approve, promote, rollback expr:^/models/
# Separation of duties: nobody approves a model they trained
deny role release-manager approve expr:^/models/ if trained_by == request_user
[rolepolicy]
grant group ml-team ml-engineer
grant user dana release-manager

엔지니어는 등록할 수 있지만 프로모션할 수 없으며, 릴리스 관리자는 trained_by가 요청 사용자인 모델을 승인할 수 없습니다.

[service.crm]
[policy]
# Check 1: the agent, only while its verified token covers the request
grant role in-scope read, update expr:^/tickets/
grant role in-scope refund expr:^/orders/
# Check 2: the delegating user (the token's sub), with their roles now
grant role support read, update expr:^/tickets/
grant role support refund expr:^/orders/ if amount <= 100
# Larger refunds: a verified approval by someone other than the user
grant role support refund expr:^/orders/ if approved_by != request_user
[rolepolicy]
# Check 1 in three steps, each role needing the one before:
# the token has not expired,
grant entity triage-agent in-time if request_time < token_expires
# it lists this action,
grant role in-time in-action if request_action in token_actions
# and it lists this resource
grant role in-action in-scope if request_resource in token_resources
# Check 2: the user's own role
grant user alice support

첫 번째 확인은 에이전트에 3단계로 역할을 부여하여 토큰 만료 전이자 토큰의 액션과 리소스에만 유효하도록 제한합니다. 두 번째 확인은 사용자 자신을 검증하므로 사용자 역할이 취소되면 다음 요청에서 에이전트도 거부됩니다. 100을 초과하는 환불은 사용자가 아닌 승인자가 필요합니다.

GitHub에서 두 패턴의 실행 가능한 샘플 보기

[service.mcp-gateway]
[policy]
# Tool arguments arrive as attributes and are checked before the tool runs
grant role research-agent call /tools/web-search
grant role billing-agent call /tools/issue-refund if amount <= 100 && customer_verified == true
# Admin tools stay out of reach for research agents
deny role research-agent call expr:^/tools/admin/
[rolepolicy]
grant entity agent-research-1 research-agent
grant entity agent-billing-1 billing-agent

연구 에이전트를 위한 웹 검색, 청구 에이전트를 위한 인증된 고객 대상 최대 100 환불, 연구 에이전트에 대한 관리자 도구 명시적 거부.

[service.a2a]
[policy]
# A callee gets only scopes the caller already holds, within two hops
grant role planner-agent call /agents/researcher if IsSubSet(requested_scopes, caller_scopes) && hops <= 2
grant role researcher-agent call /agents/writer if IsSubSet(requested_scopes, caller_scopes) && hops <= 2
[rolepolicy]
grant entity planner-1 planner-agent
grant entity researcher-1 researcher-agent

IsSubSet은 호출자가 보유하지 않은 요청 범위를 거부하며, 세 번째 홉은 거부됩니다.

[service.zsp]
[policy]
# A just-in-time token: positive lifetime up to 600 s, inside its validity window, unused
# request_time defaults to the ADS clock; attributes passed by the enforcement point take precedence
# 60 s is the explicit clock-skew allowance
grant role agent-runtime invoke /api/orders if expires_at > issued_at && expires_at - issued_at <= 600 && issued_at <= request_time + 60 && not_before <= request_time + 60 && request_time < expires_at && TokenUnused(token_id)
[rolepolicy]
grant entity agent-billing-1 agent-runtime

GitHub에서 완전한 실행 가능 샘플 보기