🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows no direct signs of malicious activity but raises concerns due to metadata issues such as a non-secure link and missing git repository, alongside the novelty of both the package and its maintainer.

Non-secure link present
Git repository unavailable
Novelty of package and maintainer

Per-check LLM notes

Network: No network calls detected, which is normal unless the package relies on external services.
Shell: No shell execution detected, indicating the package does not perform any system command executions.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The presence of a non-secure link and the unavailability of the git repository raise concerns, as does the novelty of both the package and its maintainer.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ 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 score 2.0

Found 1 suspicious link(s) on the package page

Non-HTTPS external link: http://127.0.0.1:3000/dashboard

⚠ Git Repository History score 3.0

Repository not found (deleted or private)

Repository not found (deleted or private)

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Only one version has ever been released — brand new package
Author "Agent Grid Protocol Team" 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 agent-grid-protocol

Create a mini-application called 'AI Quota Manager' using Python, which leverages the 'agent-grid-protocol' package to manage autonomous AI API quotas and tokens efficiently. This application will serve as a personal dashboard where users can view their current API usage across various services, exchange tokens when necessary, and monitor their quota limits.

Step 1: Setup the Project Environment
- Initialize a new Python project.
- Install the required packages including 'agent-grid-protocol'.

Step 2: Authentication Module
- Implement a secure login system for users to authenticate themselves before accessing the service.
- Use environment variables to store sensitive information like API keys.

Step 3: Dashboard Creation
- Design a simple UI (using libraries like Tkinter or Streamlit) where users can see their current API usage statistics.
- Display real-time data fetched from different services using the 'agent-grid-protocol' package.

Step 4: Quota Management
- Integrate the 'agent-grid-protocol' package to allow users to check their remaining quota for each service.
- Provide notifications when the quota reaches a critical level.

Step 5: Token Exchange Feature
- Implement a feature that allows users to exchange tokens when they run out of quota.
- Utilize the 'agent-grid-protocol' package's token exchange functionality.

Suggested Features:
- Historical Usage Reports: Allow users to generate reports showing their API usage over time.
- Service Comparison: Enable users to compare their usage across different services.
- Alerts: Set up customizable alerts for low quota levels or excessive usage.

How 'agent-grid-protocol' is Utilized:
- The package's core functionalities are used to interact with the autonomous AI API services, fetch quota information, and manage token exchanges seamlessly.