aprisma

v0.1.4 suspicious
6.0
Medium Risk

A production-grade Python Prisma client

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has a moderate risk score due to the use of subprocess for shell execution and concerns over its metadata.

  • High shell risk due to subprocess usage
  • Suspicious metadata indicating potential supply-chain attack
Per-check LLM notes
  • Network: No network calls detected, which is neutral.
  • Shell: Use of subprocess to execute shell commands could indicate potential for executing arbitrary code, suggesting higher risk.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
  • Metadata: The package shows signs of being potentially suspicious due to its newness, lack of maintainer information, and minimal repository activity.

📦 Package Quality Overall: Medium (5.8/10)

✦ High Test Suite 9.0

Test suite present — 28 test file(s) found

  • Test runner config found: conftest.py
  • Test runner config found: pyproject.toml
  • 28 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://xLaszlo.github.io/aprisma
  • Detailed PyPI description (4811 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

  • 81 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 23 commits in xLaszlo/aprisma
  • Two distinct contributors found

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 4.0

Found 2 shell execution pattern(s)

  • .mktemp("db") / "test.db" subprocess.run( [ "npx", "--yes",
  • cept-data-loss"] result = subprocess.run(cmd, capture_output=True, text=True) if result.returncod
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: users.noreply.github.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • 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 aprisma 
Create a fully-functional mini-application named 'PrismaBlog' that leverages the 'aprisma' package to manage a simple blogging platform. This application should allow users to create, read, update, and delete blog posts, as well as follow other users and like/dislike posts. The application should also have a feature for displaying popular and recent posts on the homepage.

Step-by-Step Instructions:
1. Set up your development environment with Python installed and create a new virtual environment.
2. Install 'aprisma' and any other necessary packages such as FastAPI for the backend and an appropriate frontend framework/library of your choice.
3. Define the database schema using aprisma's schema language, including models for User, Post, Like, and Follow relationships.
4. Implement CRUD operations for Posts through API endpoints using FastAPI. Ensure each endpoint is secure and authenticated.
5. Add functionality for users to follow other users and like/dislike posts. Track these interactions in the database.
6. Develop the frontend to interact with the backend APIs, allowing users to view their profile, follow/unfollow other users, like/dislike posts, and navigate between different categories of posts.
7. Implement pagination for post listings to improve performance and user experience.
8. Create an admin panel where you can monitor and manage user activities, including the ability to delete spam or inappropriate content.
9. Test the application thoroughly, ensuring all features work as expected and the application is secure against common web vulnerabilities.
10. Deploy the application to a cloud service provider such as Heroku or AWS, ensuring it's accessible over HTTPS.

Suggested Features:
- User authentication with JWT tokens for secure access.
- Real-time notifications when someone likes/dislikes a post or follows a user.
- Search functionality for posts based on title and content.
- Ability to upload images and attach them to posts.
- Analytics dashboard showing post popularity and user engagement.

Utilizing 'aprisma':
- Use aprisma's powerful query capabilities to efficiently fetch related data (e.g., posts from followed users).
- Leverage aprisma's transactional support to ensure consistency during complex operations like following a user and liking a post simultaneously.
- Implement aprisma's caching mechanisms to optimize performance for frequently accessed data.

💬 Discussion Feed

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