app-verification-suite

v0.0.5 safe
3.0
Low Risk

(No description)

🤖 AI Analysis

Final verdict: SAFE

The package appears to be safe with no direct evidence of malicious intent. While there is potential misuse of shell execution and some concerns about metadata, these alone do not strongly indicate a supply-chain attack.

  • Low network and obfuscation risks
  • Potential misuse of shell execution
  • Concerns about metadata suggest new or inactive maintainer
Per-check LLM notes
  • Network: No network calls detected, which is low risk.
  • Shell: Shell execution may be part of legitimate functionality but requires further investigation to ensure it's not being misused.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows signs of being potentially new or from an inactive maintainer, raising some concerns.

📦 Package Quality Overall: Low (4.8/10)

✦ High Test Suite 9.0

Test suite present — 16 test file(s) found

  • 16 test file(s) detected (e.g. test_calibration.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (7664 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 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 312 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 score 2.0

Found 1 shell execution pattern(s)

  • , green, blue = rgb_color subprocess.run( [ "ffmpeg", "-y",
✓ 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 app-verification-suite 
Create a mini-application named 'DepthAI Recorder' using the Python package 'app-verification-suite'. This application will allow users to record input data from DepthAI applications and save it into a dataset for later use. Additionally, the application should have the capability to replay these saved datasets back into a DepthAI pipeline for testing purposes. Here are the key features your application should include:

1. **Data Recording Mode**: Enable users to switch the application into recording mode where it captures input data from a running DepthAI application and stores it in a specified format within a dataset.
2. **Dataset Management**: Implement a user-friendly interface to manage datasets, including viewing details of each dataset, deleting unwanted ones, and renaming them.
3. **Replay Mode**: Allow users to select a recorded dataset and replay it through a DepthAI pipeline to test how the application behaves with previously recorded input data.
4. **Verification Feature**: After replaying a dataset, the application should compare the output against expected results (if provided), highlighting any discrepancies.
5. **Configuration Settings**: Provide options to configure various parameters such as file formats for saving datasets, output verification thresholds, etc.
6. **User Interface**: Develop a simple yet intuitive GUI using a Python framework like Tkinter or PyQt to interact with the application.
7. **Documentation**: Include comprehensive documentation detailing how to install and use the application, along with examples.

The 'app-verification-suite' package will be utilized throughout the development process, primarily for its ability to switch apps between live and replay modes, record datasets, and verify outputs. Ensure that your application leverages these functionalities effectively to provide robust testing capabilities for DepthAI applications.

💬 Discussion Feed

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