How do I secure CrewAI multi-agent systems?

CrewAI multi-agent systems are vulnerable because agents trust each other by default — compromising one agent can cascade to the entire crew. In a multi-agent architecture, agents pass context sequentially or hierarchically. If Agent A is compromised via prompt injection, every downstream agent (B, C, D) inherits the poisoned context.

Key CrewAI security risks include:

• Default trust between agents: No trust boundary enforcement between crew members
• Code Interpreter sandbox escape: Improper Docker sandbox fallbacks allowing remote code execution
• Shared .env credentials: All agents share the same production credentials
• No per-tool least privilege: Every agent can access every tool with the same permission level
• Telemetry data privacy: Agent interactions may be logged without GDPR/HIPAA compliance

The community consensus: "CrewAI should be treated as an adversarial environment rather than trusted middleware. Always build your own security layer."

Exogram provides that security layer through namespace isolation and per-action governance. Each agent in the crew operates within its own governance namespace with scoped permissions. When Agent B attempts a tool call, Exogram evaluates it against B's specific policy rules — not a shared, crew-wide permission set. Trust boundaries are deterministically enforced, not probabilistically assumed.