async-tiff

v0.7.2 safe
4.0
Medium Risk

(No description)

🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of malicious activity such as network calls, shell execution, or credential harvesting. However, it has some metadata risks due to an absent author name and a new maintainer account.

  • No network calls
  • No shell execution
  • No credential harvesting
  • Absent author name
  • New maintainer account
Per-check LLM notes
  • Network: No network calls detected, which is normal for a library focused on handling TIFF images asynchronously.
  • Shell: No shell execution patterns detected, aligning with the expected behavior for a non-system administration related package.
  • Obfuscation: No obfuscation patterns detected, suggesting low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, indicating no immediate risk of secret theft.
  • Metadata: The package has some red flags including an absent author name and a new maintainer account, but no direct evidence of malicious intent.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 10 test file(s) found

  • Test runner config found: pyproject.toml
  • Test runner config found: conftest.py
  • 10 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (2378 chars)
○ 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

  • 27 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 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

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" 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 async-tiff 
Develop a small, fully-functional mini-application called 'TiffExplorer' that leverages the 'async-tiff' package to handle large TIFF image files efficiently. The application should allow users to asynchronously load, view, and manipulate multi-page TIFF images without blocking the main thread, ensuring smooth user interaction. Here’s a detailed breakdown of the steps and features to implement:

1. **Setup**: Start by installing the 'async-tiff' package using pip. Ensure your environment is set up with Python 3.8 or higher.
2. **Loading TIFF Files**: Create a function that allows users to select a TIFF file from their local system. Use the 'async-tiff' package to asynchronously read the TIFF file and display basic information such as the number of pages, dimensions, and color mode.
3. **Asynchronous Viewing**: Implement a feature where users can navigate through the pages of a multi-page TIFF file asynchronously. Display each page in a user-friendly interface, possibly using libraries like PyQt5 or PySide2 for the GUI.
4. **Manipulation Features**: Provide options to manipulate the TIFF images, such as resizing, rotating, or applying simple filters (e.g., grayscale conversion). Ensure these operations are also performed asynchronously to maintain responsiveness.
5. **Saving Changes**: Allow users to save their manipulated TIFF images either as new files or overwrite the original. Implement error handling to manage potential issues during file saving.
6. **User Interface**: Design an intuitive and responsive UI that clearly shows progress while performing asynchronous tasks, such as loading or saving images.
7. **Documentation and Testing**: Write comprehensive documentation for the application and include unit tests for all major functionalities to ensure reliability.

The goal is to showcase the power of 'async-tiff' in handling large image files efficiently and to provide a practical tool for users dealing with TIFF images.

💬 Discussion Feed

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