AI Analysis
Final verdict: SAFE
The package exhibits very low risks across multiple categories, with no signs of malicious activities or supply-chain attacks. The metadata risk is slightly elevated due to the maintainer's limited presence and repository recognition.
- No network or shell execution detected.
- Low risk of obfuscation or credential harvesting.
- Maintainer has only one package and the repository is not widely recognized.
Per-check LLM notes
- Network: No network calls detected, which is normal for a database manipulation library.
- Shell: No shell execution patterns detected, aligning with the expected behavior of a database handling package.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has only one package and the repository is not widely recognized.
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 2.0
1 maintainer concern(s) found
Author "Bendik Rønning Opstad" 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 PyDbLite3
Create a simple inventory management system using the PyDbLite3 package. This system will allow users to add, delete, update, and search for items in their inventory. Each item in the inventory should have at least the following fields: ID (unique identifier), name, category, quantity, and price. Step-by-step instructions: 1. Install the PyDbLite3 package if it isn't already installed. 2. Create a new database file named 'inventory.db' and define the structure of the database table with the specified fields. 3. Implement functions to add new items to the inventory, ensuring that each item has a unique ID. 4. Add functionality to delete items from the inventory based on the ID. 5. Develop a feature to update existing items in the inventory, allowing changes to any of the fields except the ID. 6. Integrate a search function that allows users to find items by entering keywords related to the item's name, category, or ID. 7. Implement a feature to display all items in the inventory. 8. Optionally, enhance the application by adding features such as sorting items by price or category, exporting the inventory to a CSV file, or importing an existing CSV file into the inventory. In your implementation, demonstrate how PyDbLite3 is utilized to manage the database operations efficiently and effectively. Pay special attention to handling exceptions and ensuring data integrity.