anporia-client

v0.2.0 suspicious
4.0
Medium Risk

Python client for ANP2 — the economic protocol for AI agents (identity + reputation + credit + Sybil resistance)

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks in direct threats such as shell execution, obfuscation, and credential harvesting. However, the metadata risk score and the unavailability of the repository raise concerns about its legitimacy and maintenance.

  • Metadata risk score of 5/10
  • Repository not found
  • Single package from maintainer
Per-check LLM notes
  • Network: The network call pattern suggests the package is likely making authenticated HTTP requests, which is common for client packages communicating with a service.
  • Shell: No shell execution patterns detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting the package does not pose a risk for stealing secrets or credentials.
  • Metadata: The package has no typosquatting or email domain flags, but the repository is not found and the maintainer has only one package, indicating potential risks.

📦 Package Quality Overall: Low (4.2/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 1 test file(s) detected (e.g. test_client.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://anp2.com/docs
  • Detailed PyPI description (2730 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 35 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • (u, p) self._client = httpx.Client(timeout=timeout, auth=auth) # ---------- identity -----
✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "ANP2 contributors" 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 anporia-client 
Develop a mini-application called 'AI Marketplace' that leverages the 'anporia-client' package to facilitate secure transactions between AI agents. This application will serve as a platform where AI agents can offer their services, and other agents or users can purchase these services securely. Here are the key steps and features of the application:

1. **Setup and Configuration**: Begin by installing the 'anporia-client' package and setting up the necessary configurations for identity management, reputation tracking, and credit handling.

2. **User Registration and Identity Management**: Implement a feature where AI agents can register on the platform using the 'anporia-client'. Each agent should have a unique identity managed through the ANP2 protocol.

3. **Service Listings**: Allow registered AI agents to list their services along with descriptions, pricing, and any relevant credentials verified through the anporia-client's reputation system.

4. **Transaction Handling**: Integrate the payment system using the anporia-client's credit mechanism. Ensure all transactions are tracked and secured according to the ANP2 protocol.

5. **Reputation System**: Develop a system where buyers can rate and review services they purchase from AI agents. These ratings will contribute to the overall reputation score of each agent, which is managed through the anporia-client.

6. **Sybil Resistance**: Implement measures to prevent Sybil attacks using the anporia-client's Sybil resistance features, ensuring the integrity of the marketplace.

7. **Security Enhancements**: Secure the communication between the AI agents and the marketplace using the anporia-client's encryption capabilities.

8. **Dashboard**: Create a dashboard for each AI agent where they can view their service listings, transaction history, and reputation scores.

By following these steps, you'll create a robust and secure marketplace for AI services that leverages the advanced features of the 'anporia-client' package.

💬 Discussion Feed

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