Authorize CrewAI multi-agent tool access with Cerbos
Enforce per-agent and per-tool authorization across CrewAI crews using Cerbos policy evaluation.
Per-agent tool authorization
Control which tools each CrewAI agent can invoke with fine-grained Cerbos policies based on agent role and task context
Context-aware decisions
Authorize tool calls based on agent identity, assigned role, task attributes, and runtime context
Multi-agent audit trail
Every authorization decision across all agents is logged with full context for compliance and debugging
How Cerbos works with CrewAI
AI agents and tools introduce a new class of authorization challenges. They act on behalf of users, access sensitive data, and chain operations, all of which need fine-grained access control.
Cerbos provides policy-driven authorization that controls what AI systems can do, which data they can access, and on whose behalf. Policies are written in human-readable YAML and evaluated at request time.
With Cerbos and CrewAI, you get guardrails that scale with your AI adoption, centrally managed policies, full audit trails, and sub-millisecond decision times that don't slow down agent workflows.
How Cerbos authorizes CrewAI agents
- Define policies for each agent's tool access, Write YAML policies that specify which tools each agent role can invoke, based on identity, task, and context.
- Agent requests authorization before each tool call, Before invoking a tool, the CrewAI agent sends its identity, the tool name, and the target resource to the Cerbos PDP.
- Cerbos evaluates the request against policies, The PDP applies fine-grained rules considering the agent's role, the task being performed, and any additional attributes you provide.
- Tool call proceeds or is blocked, Cerbos returns an allow or deny decision. The application enforces it, with every decision logged for audit.
FAQ
How does Cerbos authorize CrewAI agent tool calls?
Before a CrewAI agent invokes a tool, the application sends the agent's identity, the tool name, and the target resource to the Cerbos PDP. Cerbos evaluates fine-grained policies and returns an allow or deny decision, ensuring each agent only uses tools it is authorized for.
Can I assign different permissions to different agents in a crew?
Yes. Cerbos policies are attribute-based, so each agent in a crew can have distinct tool permissions based on its role, the task it is performing, or any other context you provide.
Does Cerbos provide an audit trail for multi-agent workflows?
Yes. Every authorization decision is logged with the requesting agent, tool, resource, and result, giving you a complete audit trail across all agents in a crew.
Learn more about Cerbos
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Cerbos + CrewAI
- Cerbos policies govern AI agent tool access and data visibility
- Full audit trail for every AI tool call and data access
- Per-user permissions enforced across autonomous agent workflows
- Sub-millisecond policy evaluation with no agent pipeline overhead
Authorization for AI systems
By industry
By business requirement
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What is Cerbos?
Cerbos is an end-to-end enterprise authorization software for Zero Trust environments and AI-powered systems. It enforces fine-grained, contextual, and continuous authorization across apps, APIs, AI agents, MCP servers, services, and workloads.
Cerbos consists of an open-source Policy Decision Point, Enforcement Point integrations, and a centrally managed Policy Administration Plane (Cerbos Hub) that coordinates unified policy-based authorization across your architecture. Enforce least privilege & maintain full visibility into access decisions with Cerbos authorization.