agent-alignment-protocol

v2.0.0 suspicious
4.0
Medium Risk

Agent Alignment Protocol - The missing alignment layer for the agent protocol stack

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits low risks in terms of network usage, shell execution, and obfuscation. However, the metadata risk due to the maintainer's new or inactive account and lack of a proper author name raises some suspicion.

  • Maintainer has a new or inactive account
  • Lack of proper author name
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires network interactions for its functionality.
  • Shell: No shell executions detected, indicating no immediate risk of command execution from the package.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has a new or inactive account and lacks a proper author name, which raises some suspicion but does not conclusively indicate malice.

🔬 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

Email domain looks legitimate: mnemom.ai>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository mnemom/aap appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" 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-alignment-protocol 
Create a mini-application named 'AlignmentSimulator' using the Python package 'agent-alignment-protocol'. This application will simulate the interaction between an AI agent and its environment, focusing on ensuring the agent's actions align with predefined ethical guidelines. The goal is to demonstrate how the 'agent-alignment-protocol' package can be integrated into a real-world scenario to enhance safety and reliability of AI systems.

Step-by-step instructions:
1. Set up the project environment and install necessary packages including 'agent-alignment-protocol'.
2. Define a simple environment where the AI agent can operate, such as a grid world with obstacles and goals.
3. Implement an AI agent capable of navigating through the environment. The agent should have basic decision-making capabilities.
4. Integrate the 'agent-alignment-protocol' package to monitor and guide the agent's behavior, ensuring it adheres to ethical guidelines set by the user.
5. Develop a user interface (UI) that allows users to interact with the simulation, including setting up scenarios, adjusting ethical guidelines, and observing the agent's performance.
6. Incorporate feedback mechanisms within the UI to allow users to evaluate the agent's behavior and provide adjustments if necessary.
7. Ensure the application logs all interactions and decisions made by the agent for review and analysis.

Suggested Features:
- Customizable ethical guidelines that can be adjusted based on different scenarios.
- A visual representation of the environment and the agent's path.
- Detailed logs of the agent's decisions and their alignment with ethical guidelines.
- User-friendly UI for easy interaction and scenario setup.
- Real-time feedback and adjustment options for ethical guidelines during runtime.

How 'agent-alignment-protocol' is utilized:
- The package provides a framework for defining and enforcing ethical guidelines. In this application, these guidelines will serve as constraints for the agent's decision-making process.
- Utilize the package's monitoring tools to continuously assess the agent's behavior against the defined ethical standards.
- Leverage the package's feedback mechanisms to adjust the agent's behavior dynamically based on user input and observed outcomes.

This project aims to showcase the practical application of ethical considerations in AI development and operation, highlighting the importance of alignment protocols in building trustworthy AI systems.