AI Analysis
Final verdict: SUSPICIOUS
The package has minimal risks based on the checks performed but is newly created with limited maintainer history and no associated GitHub repository, raising concerns about its origin and purpose.
- Metadata risk due to new creation and lack of maintainer history/repo.
- No immediate technical risks identified.
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires external services.
- Shell: No shell execution patterns detected, indicating no immediate risk of command injection or similar attacks.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
- Credentials: No credential harvesting patterns detected, indicating low risk of secret or credential theft.
- Metadata: The package is newly created with limited maintainer history and no associated GitHub repository, which raises some suspicion.
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
Email domain looks legitimate: allfly.io
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
Only one version has ever been released — brand new packageAuthor "Allfly" 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 af-db-types-json
Create a mini-application that manages a simple inventory system using Python's Flask framework and integrates the 'af-db-types-json' package for enhanced data handling. The application should allow users to add, update, delete, and view items in the inventory. Each item will have attributes such as name, category, quantity, price, and a custom JSON field for additional metadata like specifications or notes. The core functionalities of the app include: - Adding new items to the inventory with all specified fields. - Updating existing items with new details. - Deleting items from the inventory. - Viewing all items in the inventory or specific items based on search criteria. To utilize the 'af-db-types-json' package, you will need to define Pydantic models that correspond to the JSON fields in your database schema. These models will provide type checking, validation, and serialization/deserialization capabilities for the JSON data stored in your PostgreSQL database using SQLAlchemy's JSONB column type. For example, create a Pydantic model for the 'metadata' field that includes specific attributes like warranty information or dimensions. The application should also feature a user-friendly interface for interacting with the inventory, perhaps using HTML templates rendered by Jinja2. Additionally, consider implementing basic authentication to secure access to the inventory management functions. This project aims to showcase the power of combining Flask's simplicity with SQLAlchemy's robust ORM capabilities, while leveraging the 'af-db-types-json' package to handle complex JSON data types efficiently.