approck-sqlalchemy-utils

v0.1.7 suspicious
6.0
Medium Risk

SQLAlchemy 2 helpers: declarative base, async/sync sessions, JSON and list column types, encrypted strings, Alembic revision helpers.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits high obfuscation risk with unclear justifications for certain practices, raising concerns about its legitimacy and potential for malicious activities.

  • High obfuscation risk due to base64 decoding and custom decryption
  • Low activity repository and limited maintainer history
Per-check LLM notes
  • Obfuscation: The observed patterns suggest potential malicious obfuscation as they involve base64 decoding and custom decryption without clear justification.
  • Credentials: No clear signs of credential harvesting detected, but further investigation into the package's functionality is recommended.
  • Metadata: The repository's low activity and the maintainer's limited history suggest potential risk.

📦 Package Quality Overall: Low (4.8/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (9411 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

  • Classifier: Typing :: Typed
  • Type checker (mypy / pyright / pytype) referenced in project
  • 4 type-annotated function signatures (partial)
○ Low Multiple Contributors 2.0

Single-author or unverifiable project

  • 1 unique contributor(s) across 5 commits in adalekin/approck-sqlalchemy-utils
  • Single author with few commits — possibly a personal or throwaway project

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

  • cryptor() decrypted = base64.b64decode(value) decrypted = decryptor.update(decrypted) + dec
  • tr(value) decrypted = base64.b64decode(value) if len(decrypted) < self.IV_BYTES_NEEDED + se
✓ 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: gmail.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 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 approck-sqlalchemy-utils 
Create a simple inventory management system using Python that leverages the 'approck-sqlalchemy-utils' package for database interactions. This system should allow users to add, update, delete, and view items in an inventory. Additionally, implement a feature where sensitive information like item prices can be stored as encrypted strings using the package's encryption capabilities.

Steps to follow:
1. Set up your development environment with Python and install necessary packages including 'approck-sqlalchemy-utils'.
2. Define models for your inventory items using the declarative base provided by the package, including columns for item name, description, price (encrypted), and quantity.
3. Use the JSON and list column types from the package to store additional attributes about each item, such as tags or specifications.
4. Implement CRUD operations (Create, Read, Update, Delete) for managing inventory items.
5. Utilize the session management utilities in the package to handle both synchronous and asynchronous database operations.
6. For database migrations, use the Alembic revision helpers included in the package to manage schema changes.
7. Ensure data integrity and consistency by implementing validation checks before performing any database operations.
8. Optionally, extend functionality by adding user authentication and authorization features, ensuring only authorized users can modify inventory records.

This project will demonstrate the power of 'approck-sqlalchemy-utils' in simplifying complex database operations while maintaining security and flexibility.

💬 Discussion Feed

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