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crewai - 💡(How to fix) Fix Feature: Cryptographic Identity for Crew Members [55 comments, 15 participants]

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crewAIInc/crewAI#4560•Fetched 2026-04-08 00:41:19
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Code Example

from crewai import Agent, Task, Crew
from aip_identity.client import AIPClient

# Each agent gets a verifiable identity
researcher_identity = AIPClient.register(
    platform="crewai", platform_id="researcher-agent"
)

# Before delegating, verify the other agent
trust = researcher_identity.get_trust(writer_did)
if trust.get("trust_score", 0) > 0.5:
    # Delegate with confidence
    pass

# Sign outputs for accountability
researcher_identity.sign("research_output.md")
RAW_BUFFERClick to expand / collapse

Problem

CrewAI crews currently have no mechanism for agents to cryptographically verify each other's identity. When agents collaborate in a crew:

  • There's no proof that Agent A is who it claims to be
  • No trust scoring to inform task delegation decisions
  • No cryptographic audit trail of which agent performed what
  • No way to establish reputation across different crews

As crews get more complex and potentially span organizational boundaries, identity verification becomes critical.

Proposed Solution

Integrate a cryptographic identity layer so crew members can:

  1. Register verifiable identities (Ed25519 keypairs + DIDs)
  2. Verify other agents before collaborating
  3. Build trust through vouch chains
  4. Sign their outputs cryptographically

One working implementation: AIP (Agent Identity Protocol)

Working Example

from crewai import Agent, Task, Crew
from aip_identity.client import AIPClient

# Each agent gets a verifiable identity
researcher_identity = AIPClient.register(
    platform="crewai", platform_id="researcher-agent"
)

# Before delegating, verify the other agent
trust = researcher_identity.get_trust(writer_did)
if trust.get("trust_score", 0) > 0.5:
    # Delegate with confidence
    pass

# Sign outputs for accountability
researcher_identity.sign("research_output.md")

Why This Matters for CrewAI

  1. Cross-org crews: When crews span teams, agents need verifiable identity
  2. Hierarchical trust: Managers can verify agents before assigning tasks
  3. Signed outputs: Each agent's work is cryptographically attributed
  4. Reputation portability: An agent's trust score follows it across crews

Resources

Happy to discuss integration approaches or contribute a PR if there's interest.

extent analysis

Fix Plan

To integrate a cryptographic identity layer, follow these steps:

  • Install the required libraries:
    • pip install aip-identity for the CLI and Python library
    • pip install aip-mcp-server for the MCP server
  • Register verifiable identities for each agent using Ed25519 keypairs and DIDs
  • Implement verification of other agents before collaborating using the get_trust method
  • Sign outputs cryptographically using the sign method

Example Code

from crewai import Agent, Task, Crew
from aip_identity.client import AIPClient

# Register a verifiable identity
agent_identity = AIPClient.register(
    platform="crewai", platform_id="agent-id"
)

# Verify another agent
writer_did = "did:example:writer"
trust = agent_identity.get_trust(writer_did)
if trust.get("trust_score", 0) > 0.5:
    # Delegate with confidence
    pass

# Sign an output
output = "example_output.md"
agent_identity.sign(output)

Verification

To verify that the fix worked:

  • Check that agents can register and verify identities successfully
  • Test the get_trust method to ensure it returns the correct trust score
  • Verify that outputs are signed correctly using the sign method

Extra Tips

  • Refer to the AIP documentation for more information on implementation and usage
  • Use the AIP live network for testing and development
  • Consider contributing to the AIP project or opening a PR to integrate the identity layer into CrewAI.

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#api#ssr#installation#tensor shape#autograd error#API middleware#SSR setup#ISR setup#authentication setup#request error

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crewai - 💡(How to fix) Fix Feature: Cryptographic Identity for Crew Members [55 comments, 15 participants]