AI Analysis
Final verdict: SAFE
The package appears to be safe with no detected network, shell execution, obfuscation, or credential risks. While there are some concerns regarding metadata, such as the author's incomplete information and the maintainer's account status, these do not strongly indicate malicious intent.
- No network calls detected
- Inactive or new maintainer account
- Author's name is missing or too short
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires network functionality.
- Shell: No shell execution patterns detected, indicating no immediate risk of unauthorized command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows some red flags including an author with a missing or very short name and an inactive or new maintainer account, but there are no clear signs of typosquatting or malicious intent.
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: 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 shortAuthor "" 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 DAOModel
Create a simple inventory management system using Python and the 'DAOModel' package. This system should allow users to manage a list of products including their names, quantities, and prices. Additionally, the system should support basic CRUD operations (Create, Read, Update, Delete) for managing product data efficiently. ### Features: - **Product Management**: Add new products, update existing ones, view details, and remove products from the inventory. - **Search Functionality**: Implement search capabilities to find products based on name or price range. - **User Interface**: Design a command-line interface for interacting with the system. - **Data Persistence**: Use 'DAOModel' to automatically handle database operations without writing raw SQL queries. ### Steps: 1. **Setup Project Environment**: - Install necessary packages, including 'DAOModel'. - Define a Product model class that includes fields such as `name`, `quantity`, and `price`. 2. **Implement CRUD Operations**: - Create functions to add, retrieve, update, and delete products. 3. **Integrate Search Functionality**: - Develop a search function that allows users to look up products by name or within a specified price range. 4. **Build Command-Line Interface**: - Utilize Python's built-in libraries to create a user-friendly CLI for interacting with the inventory system. 5. **Test the Application**: - Thoroughly test each feature to ensure functionality and data integrity. 6. **Document the Code**: - Provide comments and documentation within the codebase explaining key functionalities and how 'DAOModel' is utilized. ### How 'DAOModel' is Utilized: - 'DAOModel' will be used to automatically generate the Data Access Object (DAO) layer for the Product model. This means you won't need to manually write any SQL or ORM mappings. Instead, you'll focus on defining your business logic and leveraging the provided DAO methods for database interactions.
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