AI Analysis
Final verdict: SUSPICIOUS
The package shows minimal direct risks but raises concerns due to the maintainer's limited presence and lack of a GitHub repository, suggesting potential unreliability or suspicious intent.
- metadata risk due to single package and no associated GitHub
- low but present indicators across other categories
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires external API interactions.
- Shell: No shell execution patterns detected, indicating no immediate risk of executing arbitrary commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
- Credentials: No credential harvesting patterns detected, indicating low risk of credential theft.
- Metadata: The maintainer has only one package and no associated GitHub repository, which could indicate a less established or potentially suspicious activity.
Package Quality Overall: Low (2.0/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
○ Low
Documentation
1.0
No documentation detected
No documentation URL, doc files, or meaningful description found
○ Low
Contributing Guide
2.0
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium
Type Annotations
5.0
Partial type annotation coverage
5 type-annotated function signatures (partial)
○ Low
Multiple Contributors
1.0
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
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: wearcane.com
Suspicious Page Links
All external links appear legitimate
Git Repository History
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Arcane" 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 arcane-facebook
Create a social media monitoring tool using Python and the 'arcane-facebook' package. This tool will allow users to monitor their Facebook page for new posts, comments, and reactions in real-time. Additionally, it will provide insights into engagement metrics such as likes, shares, and comments on specific posts. Here’s how you can structure your project: 1. **Setup**: Begin by setting up your development environment. Ensure Python is installed and create a virtual environment. Install the necessary packages including 'arcane-facebook'. Also, include other relevant libraries like Flask for web serving and threading for background tasks. 2. **Authentication**: Integrate Facebook API authentication within your application. Use OAuth 2.0 for secure access tokens retrieval and manage them securely within your app. 3. **Data Fetching**: Utilize 'arcane-facebook' to fetch data from Facebook pages. Start by implementing functions to retrieve recent posts, comments, and reactions. These functions should be designed to handle pagination and rate limiting imposed by the Facebook API. 4. **Real-Time Monitoring**: Implement a feature to continuously monitor Facebook pages for new activity. Use threading or asynchronous programming techniques to ensure the application remains responsive while performing background tasks. 5. **Engagement Insights**: Develop a dashboard that displays key engagement metrics such as likes, shares, and comments. Use Flask to serve these insights via a web interface. Make sure the dashboard is user-friendly and visually appealing. 6. **Notifications**: Add a notification system to alert users about significant changes such as when a post receives more than a certain number of likes or comments. Consider integrating email or SMS services for notifications. 7. **Testing & Documentation**: Thoroughly test each component of your application to ensure reliability. Write comprehensive documentation detailing how to set up and use the tool, including any prerequisites and setup instructions. 8. **Deployment**: Finally, deploy your application to a cloud service provider such as Heroku or AWS. Ensure the deployment process is smooth and the application runs efficiently in a production environment.
💬 Discussion Feed
No discussion yet. Be the first to share your thoughts!
Report Abuse / Security Issue