aquarium-python-api

v2.2.3 safe
3.0
Low Risk

Aquarium python package

🤖 AI Analysis

Final verdict: SAFE

The package aquarium-python-api v2.2.3 is deemed safe based on the analysis notes provided. There are no significant risks identified, and the network, shell, obfuscation, and credential risks are all low.

  • Low network risk as expected for a package interacting with an external service.
  • No signs of malicious activity such as shell execution, obfuscation, or credential harvesting.
Per-check LLM notes
  • Network: Network calls to an API are expected if the package is designed to interact with an aquarium-related service or data source.
  • Shell: No shell execution patterns were detected, indicating no immediate risk associated with command execution.
  • 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 engage in unauthorized secret collection.
  • Metadata: The maintainer has only one package, which may indicate a new or less active account, but there are no other red flags.

📦 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 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.python.aquarium.app
  • Detailed PyPI description (1740 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 100 commits in fatfish-lab/aquarium-python-api
  • Two distinct contributors found

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • Session self.session=requests.Session() self.api_url=api_url self.api_version=api
✓ 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: fatfi.sh

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository fatfish-lab/aquarium-python-api appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Fatfish Lab" 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 aquarium-python-api 
Create a monitoring dashboard application using Python that leverages the 'aquarium-python-api' package. This application will serve as a real-time monitoring tool for various system metrics such as CPU usage, memory usage, disk space, network traffic, and more. It should be designed to run on a local machine or server, providing insights into the health and performance of the system.

Step 1: Set up the project environment.
- Install Python and necessary libraries including 'aquarium-python-api'.
- Initialize a new virtual environment for your project.

Step 2: Define the main functionalities.
- Implement functions to fetch system metrics using 'aquarium-python-api'.
- Create a data storage mechanism to keep track of historical data.

Step 3: Develop the user interface.
- Design a simple yet effective web interface using a Python web framework like Flask or Django.
- Integrate real-time updates for system metrics.

Step 4: Add advanced features.
- Include alerts for critical thresholds (e.g., high CPU usage).
- Provide historical data visualization through graphs or charts.
- Allow users to customize which metrics they want to monitor.

How to utilize 'aquarium-python-api':
- Use the package to gather real-time data from the system.
- Explore its capabilities to monitor specific components or services.
- Utilize any additional utilities provided by the package for data processing or analysis.

💬 Discussion Feed

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