agentmesh_trust_protocol

v3.7.0 safe
3.0
Low Risk

Inter-Agent Trust Protocol (IATP) - The Envoy for AI Agents. A sidecar architecture with typed IPC pipes for preventing cascading hallucinations in autonomous agent networks.

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risk indicators and is part of a known project from Microsoft. There is no strong evidence suggesting malicious intent or supply-chain attack.

  • Low network, shell, obfuscation, and credential risks.
  • Part of a reputable project with clear documentation.
Per-check LLM notes
  • Network: Network calls to external services are common but should be reviewed for legitimacy based on the package's purpose.
  • Shell: No shell execution patterns detected.
  • Obfuscation: The observed patterns likely represent standard cryptographic operations rather than malicious obfuscation.
  • Credentials: No clear evidence of credential harvesting is present in the provided code snippets.
  • Metadata: The author has only one package, which might indicate a new or less active account, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Medium (6.8/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/microsoft/agent-governance-toolkit#readme
  • Detailed PyPI description (6967 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 86 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 14 unique contributor(s) across 100 commits in microsoft/agent-governance-toolkit
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

⚠ Outbound Network Calls score 6.0

Found 4 network call pattern(s)

  • tch the manifest with httpx.Client(timeout=timeout) as client: if verbose and not o
  • try: async with httpx.AsyncClient() as client: response = await client.post(
  • try: async with httpx.AsyncClient() as client: response = await client.post(
  • y: async with httpx.AsyncClient() as client: response = await client.pos
⚠ Code Obfuscation score 6.0

Found 3 obfuscation pattern(s)

  • try: key_bytes = base64.b64decode(raw_key) public_key_obj = Ed25519PublicKey.from_
  • signature_bytes = base64.b64decode(attestation.signature) public_key_obj.verify(sig
  • : key_bytes = base64.b64decode(private_key) private_key_obj = Ed25519Privat
✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: microsoft.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository microsoft/agent-governance-toolkit appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Microsoft Corporation" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with agentmesh_trust_protocol 
Develop a small-scale, proof-of-concept application that demonstrates the use of the 'agentmesh_trust_protocol' package to establish a secure communication network between AI agents. This application will simulate a scenario where multiple AI agents work collaboratively on a task, such as data analysis, while ensuring that no single agent can cause a failure that would cascade through the entire network due to misinformation or errors.

The application should include:
- At least three different types of AI agents (e.g., Data Collector, Analyzer, and Reporter), each with distinct roles and responsibilities.
- An inter-agent trust protocol that allows these agents to communicate securely and verify the integrity of the information they exchange.
- A mechanism for detecting and mitigating potential cascading failures caused by incorrect data or malfunctioning agents.
- A user interface that displays the status of each agent and the overall health of the network.

Key Features:
1. Agent Registration: Each agent must register with the network before it can participate, providing its type and initial state.
2. Secure Communication Channels: Implement typed IPC (Inter-Process Communication) pipes between agents to ensure that only relevant and expected data is exchanged.
3. Trust Verification: Utilize the 'agentmesh_trust_protocol' package to implement a verification system where each piece of information passed between agents is checked for authenticity and accuracy.
4. Error Handling and Recovery: If an agent detects an error or inconsistency in the data received from another agent, it should isolate itself and alert other agents about the issue without causing a network-wide failure.
5. Health Monitoring: Provide real-time monitoring of each agent's performance and network stability, highlighting any potential issues before they become critical.

How to Use 'agentmesh_trust_protocol':
- Initialize the trust protocol at the start of your application to set up the necessary infrastructure for secure communication.
- When agents send messages to each other, use the trust protocol's methods to encode the message with metadata about its origin and intended recipient.
- Upon receiving a message, each agent should use the trust protocol to decode and verify the message's integrity before processing it further.
- In case of detected errors or inconsistencies, agents should follow predefined protocols to handle the situation gracefully, such as logging the issue and isolating themselves from the network temporarily until the problem is resolved.