alayalite

v1.0.0 safe
3.0
Low Risk

AlayaLite Python extension module

🤖 AI Analysis

Final verdict: SAFE

The package has low risks across all categories with no detected network calls or shell executions. The main concern is the incomplete metadata and author details, but these alone do not indicate malicious intent.

  • Incomplete metadata and author details.
  • No network calls or shell executions detected.
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires internet access for its functionality.
  • Shell: No shell execution patterns detected, indicating the package does not execute system commands without explicit user action.
  • Metadata: Low risk but requires attention due to incomplete metadata and author details.

📦 Package Quality Overall: Low (3.8/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (10186 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 8 unique contributor(s) across 70 commits in AlayaDB-AI/AlayaLite
  • Active community — 5 or more distinct 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

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: alayadb.ai>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository AlayaDB-AI/AlayaLite appears legitimate

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" 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 alayalite 
Create a Python-based mini-app that leverages the 'alayalite' package to analyze and manipulate data from a blockchain network, specifically focusing on Ethereum transactions. This app will serve as a basic tool for users to explore their transaction history and understand various aspects of their interactions within the Ethereum ecosystem. Here’s a step-by-step guide to building this app:

1. **Setup Environment**: Begin by setting up your development environment. Ensure you have Python installed, and install the 'alayalite' package along with other necessary dependencies such as Flask for web serving.
2. **Data Retrieval**: Use 'alayalite' to fetch transaction data from a specified Ethereum address. The package should allow you to interact with the blockchain efficiently, fetching details like transaction hashes, block numbers, timestamps, and gas prices.
3. **Transaction Analysis**: Implement functionality to analyze these transactions. This could include calculating total spent, identifying patterns in spending (e.g., frequent transactions at certain times), and summarizing the transaction history.
4. **User Interface**: Develop a simple web interface using Flask where users can input an Ethereum address and view summarized transaction data. The UI should display key statistics about the transactions, allowing users to easily understand their activity on the Ethereum network.
5. **Advanced Features** (Optional): Consider adding advanced features such as visualizations of transaction volumes over time, or a comparison feature that allows users to compare their transaction history with average network transaction values.
6. **Testing and Deployment**: Thoroughly test your application to ensure it functions correctly under various conditions. Once tested, deploy your application to a server so it can be accessed online.

This project not only utilizes the core capabilities of the 'alayalite' package but also provides a practical use case for understanding and interacting with blockchain data through a user-friendly interface.

💬 Discussion Feed

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