AI Analysis
Final verdict: SUSPICIOUS
The package has a moderate risk score due to potential shell execution, which needs closer examination to confirm if it's part of legitimate functionality or poses a threat.
- Potential shell execution detected
- No other significant risks identified
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package is expected to perform network operations.
- Shell: Shell execution detected may be part of intended functionality, but requires further review to ensure it does not execute arbitrary commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
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)
console script.""" return subprocess.run( ["sqale-extract", *args], capture_output=Trthout install).""" return subprocess.run( [sys.executable, "-m", "sqale.deserialize", *args],
Credential Harvesting
No credential harvesting patterns detected
Typosquatting
No typosquatting candidates detected
Registered Email Domain
No author email provided
Suspicious Page Links
All external links appear legitimate
Git Repository History
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 6.0
3 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
Known CVE Vulnerabilities
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Use this prompt to build a project with SQaLe
Create a mini-application named 'SQaLeDBManager' that leverages the Python package 'SQaLe' to manage SQLite databases derived from the SQaLe dataset. This application should provide users with the ability to not only deserialize the SQaLe dataset into SQLite databases but also perform basic database management tasks such as querying, updating, and deleting records.
The application should have the following features:
1. **Database Creation**: Allow users to specify which datasets from the SQaLe collection they wish to convert into SQLite databases. The application will then use the 'SQaLe' package to deserialize these datasets into corresponding SQLite databases.
2. **Querying Database**: Provide a simple interface for querying the SQLite databases. Users should be able to enter SQL queries directly or choose from predefined query templates (e.g., fetching all records, filtering by specific attributes).
3. **Updating Records**: Implement functionality for updating records within the SQLite databases. Users should be able to specify which record to update and what fields to modify.
4. **Deleting Records**: Include a feature to delete records based on user input or predefined criteria.
5. **Backup and Restore**: Offer options for backing up the current state of the database and restoring it to a previous state.
6. **User Interface**: Develop a user-friendly command-line interface for interacting with the application.
7. **Documentation**: Ensure that the application comes with comprehensive documentation detailing how to install and use it, including examples of how to use the 'SQaLe' package effectively.
To utilize the 'SQaLe' package, you will first need to install it via pip. Once installed, you'll call its functions to deserialize datasets into SQLite databases. For instance, to create a database from a dataset, you might use something like `sqale.deserialize('path/to/dataset.json', 'output_database.db')`. Additionally, explore how to integrate SQLite functionalities such as connection handling, cursor operations, and transaction management within your application to enhance its capabilities.