# 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

1. **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.
2. **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.
3. **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.
4. **Tool call proceeds or is blocked**: Cerbos returns an allow or deny decision. The application enforces it, with every decision logged for audit.

### Security risks of unsecured AI agents

Without authorization at every tool call, AI agents introduce risks that traditional application security doesn't cover:

- **Privilege escalation through tools.** An agent with unrestricted tool access can perform actions the delegating user isn't authorized for — reading sensitive data, modifying resources, or invoking admin operations.
- **Incomplete identity context.** Agents often carry only a partial user reference. Without the full profile, policies can't enforce department-level, role-based, or attribute-based restrictions accurately.
- **No audit trail.** Without authorization checks at each step, there's no record of what the agent did, on whose behalf, or why it was allowed — making incident investigation and compliance reporting impossible.
- **Transitive trust.** When agents chain tool calls or delegate to other agents, permissions can expand silently if each step isn't individually authorized.

### Richer agent decisions with Cerbos Synapse

When an AI agent makes an authorization call on behalf of a user, it often includes only an agent ID or partial user reference. [Cerbos Synapse](/content/product-cerbos-synapse/index.html) enriches these requests with the full user profile from your identity provider, resource metadata from your data stores, and the agent's own constraints — so the PDP receives complete context for every decision without the agent needing to assemble it.

## 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.

## 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