AI Analysis
The package has minimal risks associated with network, shell execution, and obfuscation. However, it presents a higher metadata risk due to its lack of maintainer history and an empty git repository, raising concerns about its legitimacy and long-term support.
- metadata risk due to lack of maintainer history
- empty git repository
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 signs of executing system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
- Credentials: No credential harvesting patterns detected, suggesting the package does not pose a risk for stealing secrets or credentials.
- Metadata: The package shows signs of being potentially new or inactive with no maintainer history and an empty git repository.
Package Quality Overall: Medium (5.0/10)
Test suite present — 3 test file(s) found
3 test file(s) detected (e.g. test_demo_audit_bundle.py)
Some documentation present
Detailed PyPI description (7170 chars)
No contributing guide or governance files found
Development Status classifier >= Beta
Partial type annotation coverage
42 type-annotated function signatures detected in source
Single-author or unverifiable project
1 unique contributor(s) across 17 commits in chopmob-cloud/algovoi-audit-verifierSingle author with few commits — possibly a personal or throwaway project
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: gmail.com>
All external links appear legitimate
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a standalone Python application named 'AuditChecker' using the 'algovoi-audit-verifier' package to verify the integrity of AlgoVoi selective-disclosure audit bundles. This application should allow users to upload or input the path to an audit bundle file, and then it will use the 'algovoi-audit-verifier' package to verify the authenticity and integrity of the audit data contained within without needing to trust any AlgoVoi infrastructure. The application should have the following features: 1. User-friendly GUI: Provide a simple and intuitive graphical user interface for easy interaction. 2. File Upload/Path Input: Allow users to either drag-and-drop or browse their local filesystem to select an audit bundle file, or manually input the file path. 3. Verification Process: Utilize the 'algovoi-audit-verifier' package to perform the verification process, ensuring the audit data has not been tampered with. 4. Result Display: Clearly display the verification result to the user, indicating whether the audit bundle is valid or invalid. 5. Detailed Logs: Optionally provide an option for users to view detailed logs of the verification process for troubleshooting or auditing purposes. 6. Error Handling: Implement robust error handling to gracefully manage scenarios where the file cannot be read, the verification fails, or unexpected errors occur. 7. Help Documentation: Include comprehensive help documentation accessible from within the application, explaining how to use the app and providing context about the importance of verifying audit bundles. This project aims to demonstrate the practical application of the 'algovoi-audit-verifier' package in real-world scenarios, offering a secure and reliable way for auditors and security professionals to validate audit data independently.
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