alibabacloud-adbai20250812

v1.8.1 suspicious
4.0
Medium Risk

Alibaba Cloud ADBAI (20250812) SDK Library for Python

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows some level of obfuscation and comes from a single-package author, raising concerns about its legitimacy and potential supply-chain risks.

  • Obfuscation risk of 4/10
  • Single-package author
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires online services.
  • Shell: No shell execution detected, indicating no immediate risk from command execution.
  • Obfuscation: The obfuscation pattern may indicate an attempt to hide the true version or origin of the package, but it is not definitively malicious without more context.
  • Credentials: No clear signs of credential harvesting were detected in the provided snippet.
  • Metadata: The author has only one package, which may indicate a new or less active account, but no other red flags are 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 (1179 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
  • 68 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-adbai20250812 
Create a Python-based mini-application that integrates with Alibaba Cloud's ADBAI service through the 'alibabacloud-adbai20250812' SDK library. This application will serve as a basic AI-driven image analysis tool, allowing users to upload images and receive detailed analysis results, such as object detection, facial recognition, and scene classification.

Step 1: Set up your development environment by installing Python and the 'alibabacloud-adbai20250812' package using pip. Ensure you have an Alibaba Cloud account and obtain the necessary AccessKey ID and AccessKey Secret to authenticate API requests.

Step 2: Design the user interface. Since this is a command-line application, focus on creating an intuitive CLI with options for uploading images and selecting analysis types. Consider using libraries like argparse for parsing command-line arguments.

Step 3: Implement functionality to interact with the ADBAI service. Use the 'alibabacloud-adbai20250812' package to initialize the client and call the appropriate methods for performing image analysis. For example, use the 'DetectImage' method to analyze uploaded images.

Step 4: Handle the response from the ADBAI service. Parse the JSON response to extract relevant information about detected objects, faces, and scenes. Display this information back to the user in a readable format.

Suggested Features:
- Support for multiple image formats (JPEG, PNG).
- Option to specify regions of interest within an image for more targeted analysis.
- Detailed output including bounding boxes for objects, confidence scores, and descriptions.
- Error handling for cases where the API request fails or the image upload is unsuccessful.

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