ayn

v0.0.2 suspicious
4.0
Medium Risk

Agents You Need -- Tools to search and access the AI agents you need

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits potential credential harvesting behavior and has low maintenance indicators, possibly including a typosquatting attempt. However, there are no direct signs of malicious activity or network/shell risks.

  • credential risk due to potential retrieval of credentials from environment variables
  • metadata risk suggesting low maintenance and possible typosquatting
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external services.
  • Shell: No shell execution patterns detected, indicating no immediate signs of malicious activities.
  • Obfuscation: No obfuscation patterns were detected in the provided code snippet.
  • Credentials: The observed pattern may indicate an attempt to retrieve credentials from environment variables, which could be a risk for credential harvesting depending on how it's used.
  • Metadata: The package shows signs of low maintenance and could be a typosquatting attempt.
  • ⚠ Typosquatting target: arq

📦 Package Quality Overall: Medium (5.6/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

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

Some documentation present

  • 2 documentation file(s) (e.g. ayn.py)
  • Detailed PyPI description (4926 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

  • 80 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 10 commits in thorwhalen/ayn
  • Small but multi-author team (3–4 contributors)

🔬 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 score 2.5

Found 1 credential access pattern(s)

  • ithub_token = github_token or os.getenv("GITHUB_TOKEN") def search( self, query: str, *, limit: int
⚠ Typosquatting score 3.0

Possible typosquat of: arq

  • "ayn" is 2 edit(s) from "arq"
✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author "Thor Whalen" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with ayn 
Create a versatile command-line tool named 'AgentFinder' using the Python package 'ayn', which stands for 'Agents You Need'. This tool will serve as a centralized hub for discovering, accessing, and managing various AI agents across different platforms and services. Your task is to design and implement AgentFinder, ensuring it offers a user-friendly interface and robust functionality.

Step 1: Setup
- Begin by installing the 'ayn' package and any other necessary dependencies.
- Ensure your development environment is set up correctly for Python projects.

Step 2: Core Functionality
- Implement a feature that allows users to search for available AI agents based on keywords, categories, or specific functionalities.
- Integrate 'ayn' to fetch agent details such as capabilities, supported languages, and pricing plans directly from the platform's API.
- Provide a method for users to interact with selected agents through the command line, sending commands and receiving responses.

Step 3: Advanced Features
- Develop a caching mechanism to store frequently accessed agent information locally for faster access.
- Incorporate authentication support for secure interactions with private or premium agents.
- Enable users to rate and review agents they have used, contributing to a community-driven evaluation system.

Step 4: User Interface
- Design a clean and intuitive command-line interface that guides users through searching, selecting, and interacting with agents.
- Include help and documentation within the CLI to assist new users in understanding the tool's capabilities.

Step 5: Testing and Deployment
- Write comprehensive tests to ensure the reliability of AgentFinder.
- Prepare a deployment strategy, considering options like Docker containers for easy distribution and use.

By completing this project, you will not only utilize the 'ayn' package effectively but also contribute to the growing ecosystem of tools that make AI more accessible and manageable for developers and enthusiasts alike.

💬 Discussion Feed

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