alibabacloud-modelstudio20260210

v1.2.0 safe
4.0
Medium Risk

Alibaba Cloud ModelStudio (20260210) SDK Library for Python

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risks and no indications of malicious activities. The primary concern is the use of obfuscation techniques, which are not typical for benign packages, and the presence of a non-HTTPS link.

  • Moderate obfuscation risk
  • Non-HTTPS link present
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external API interactions.
  • Shell: No shell execution patterns detected, indicating no direct system command execution from the package.
  • Obfuscation: The obfuscation technique used is not typical for malicious purposes but could be used to hide code logic.
  • Credentials: No signs of credential harvesting detected.
  • Metadata: The package has a single author with one package, which might indicate a new or less active account. There's also a non-HTTPS link present.

📦 Package Quality Overall: Low (4.4/10)

○ 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 (1203 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Type checker (mypy / pyright / pytype) referenced in project
  • 46 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 5.0

Limited contributor diversity

  • 1 unique contributor(s) across 100 commits in aliyun/alibabacloud-python-sdk
  • Single author but highly active (100 commits)

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

  • bacloud-python-sdk" VERSION = __import__(PACKAGE).__version__ REQUIRES = [ "darabonba-core>=1.0.0, <2.0.0
✓ 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: alibabacloud.com

⚠ Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://www.apache.org/licenses/LICENSE-2.0
✓ Git Repository History

Repository aliyun/alibabacloud-python-sdk appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Alibaba Cloud SDK" 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 alibabacloud-modelstudio20260210 
Create a Python-based desktop application named 'ModelMaster' using the 'alibabacloud-modelstudio20260210' package to manage machine learning models hosted on Alibaba Cloud ModelStudio. This application should enable users to perform various tasks such as uploading new models, monitoring model performance, and generating predictions based on user input data. Here’s a detailed breakdown of the functionalities and steps to implement them:

1. **User Interface Design**: Design a simple yet intuitive GUI using Tkinter or PyQt that allows users to interact with the application easily.
2. **Authentication**: Implement a secure login system to authenticate users against their Alibaba Cloud credentials before they can access any services provided by the 'alibabacloud-modelstudio20260210' package.
3. **Model Management**:
   - **Upload Models**: Allow users to upload their trained machine learning models directly from their local system to Alibaba Cloud ModelStudio using the SDK.
   - **Monitor Performance**: Provide real-time performance metrics and logs for each uploaded model, fetched from the cloud service.
4. **Prediction Service**: Enable users to input data through the GUI and use the selected model from the cloud to generate predictions.
5. **Integration with 'alibabacloud-modelstudio20260210'**:
   - Use the SDK to establish a connection with Alibaba Cloud ModelStudio, handle authentication, and perform operations like uploading models, fetching performance data, and making predictions.
6. **Error Handling and Logging**: Ensure robust error handling and logging mechanisms are in place to capture any issues during the interaction with the cloud service.
7. **Documentation and User Guide**: Prepare comprehensive documentation detailing how to install and use the application effectively.

This project aims to streamline the process of deploying and managing machine learning models on Alibaba Cloud, providing a user-friendly interface for developers and data scientists.