What are we defending against? The core threat is agent impersonation or message tampering within a multi-agent CrewAI system. Without a cryptographically enforced chain of custody for inter-agent messages, we open the door to:
* A compromised or malicious agent injecting instructions into a high-privilege agent's message stream.
* An attacker manipulating the message bus or memory to alter task results or objectives.
* A lack of non-repudiation, making forensic analysis after a security incident impossible to trust.

CrewAI's current security model, as documented, relies heavily on role-based design and task handoffs within a crew structure. However, its inter-agent communication layer does not natively implement message signing or verification. The trust is implicit, based on the assumption that all agents within a crew are cooperative and that the runtime environment is uncompromised. This is a classic default-unsafe pattern. To enforce strict message signing, we must extend or wrap the core communication pathways.

The primary attack vectors this control mitigates are within the broader category of inter-agent trust failures:
* **Malicious Internal Agent:** An agent with defined roles and permissions goes rogue, attempting to escalate privileges by sending forged tasks to other agents.
* **Man-in-the-Middle on Memory:** Adversarial manipulation of the shared memory or context used for agent communication.
* **Task Injection via Compromised Tool:** A tool output is used to craft a fraudulent message appearing to come from a legitimate agent.

Implementing a signing protocol requires intercepting the message flow. Since CrewAI does not offer a built-in cryptographic middleware, you must create a custom `Agent` subclass or a process wrapper. The critical points are the `execute_task` method and any direct `agent_to_agent_messaging` functions. A viable, though intrusive, approach involves:

* **Key Management:** Each agent instance must have a unique key pair (or a shared secret for HMAC). This must be provisioned securely at agent initialization, not hard-coded.
* **Signing Outbound:** Override the method that sends the result/context to the next agent. The payload must include a canonical representation (e.g., a sorted JSON string of the task, result, agent ID, and timestamp) and its digital signature or MAC.
* **Verifying Inbound:** Before an agent processes a task context from another agent, it must verify the signature using the purported sender's public key (or shared secret). Invalid or missing signatures should trigger a security exception, halting the crew.
* **Nonce/Timestamp:** To prevent replay attacks, include and validate a timestamp or nonce within the signed payload.

The major capability gaps are the lack of a standard identity framework for agents and no integrated key distribution mechanism. You are essentially building a PKI for your crew. Furthermore, this adds significant overhead and complexity. A simpler, though less robust, alternative is to employ a secure, trusted channel for all inter-agent communication (e.g., all messages passed through a single, hardened, internal API that logs and verifies), but this centralizes the risk.

Without this control, your threat model must assume that any agent within the crew can impersonate any other agent at the message level. Your security then relies entirely on the correctness of the role and task definitions, which are logical controls, not cryptographic ones.