atoti-client-aws

v0.9.15 safe
3.0
Low Risk

Deprecated: use atoti-client-storage-aws instead

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risks across all assessed categories, with no indications of malicious behavior. The metadata risk is slightly elevated due to the maintainer's single package, but this alone does not suggest a supply-chain attack.

  • No network calls detected
  • Maintainer has only one package
Per-check LLM notes
  • Network: No network calls detected, which is not necessarily suspicious for a client package interacting with AWS services.
  • Shell: No shell execution patterns detected, indicating no immediate risk of executing arbitrary commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has only one package, which could 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 5.0

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.activeviam.com/products/atoti/python-sdk/0.9.15
○ 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

  • Classifier: Typing :: Typed
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 100 commits in atoti/atoti
  • Two distinct contributors found

🔬 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: activeviam.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository atoti/atoti appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "ActiveViam" 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 atoti-client-aws 
Develop a mini-data analytics dashboard that integrates data from Amazon S3 using the 'atoti-client-aws' package. Although the package has been deprecated in favor of 'atoti-client-storage-aws', let's proceed with it for educational purposes. Your task is to create a simple yet functional web-based application that allows users to load, analyze, and visualize data stored in an AWS S3 bucket. Here’s a step-by-step guide on how to build this application:

1. **Setup Project Environment**: Initialize a new Python virtual environment and install the necessary packages including 'atoti-client-aws', Flask for web serving, and any visualization libraries such as Plotly or Matplotlib.
2. **Data Integration**: Use 'atoti-client-aws' to connect to your specified S3 bucket and retrieve datasets. Ensure you handle authentication securely using AWS credentials.
3. **Data Processing**: Once the data is loaded into your application, perform basic data cleaning and preprocessing steps such as handling missing values, converting data types, and filtering out irrelevant columns.
4. **Interactive Dashboard**: Create an interactive dashboard where users can select different datasets and view them in various formats. Implement functionalities like sorting, searching, and filtering.
5. **Visualization**: Integrate Plotly or similar libraries to provide visual representations of the data. Users should be able to choose between different types of charts (e.g., bar charts, line graphs, pie charts) based on their preferences.
6. **Deployment**: Finally, deploy your application using a service like Heroku or AWS Elastic Beanstalk so others can access it over the internet.

Suggested Features:
- User Authentication: Allow users to sign up and log in to personalize their experience.
- Real-time Data Updates: Automatically update the dashboard with new data uploaded to the S3 bucket.
- Export Functionality: Provide an option to export visualizations and data tables as CSV or PDF files.
- Customizable Themes: Enable users to customize the color schemes and layouts of the dashboard.

Remember, the core functionality revolves around leveraging 'atoti-client-aws' to seamlessly integrate data from AWS S3 into your application. Focus on making the data accessible and useful through robust analysis and visualization tools.

💬 Discussion Feed

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