AI Analysis
Final verdict: SAFE
The package exhibits no signs of obfuscation or credential harvesting, and the metadata risk is relatively low despite showing signs of poor maintenance.
- No obfuscation patterns detected
- No credential harvesting patterns detected
Per-check LLM notes
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows low maintenance and metadata quality but lacks clear indicators of malicious intent.
Package Quality Overall: Medium (5.4/10)
✦ High
Test Suite
9.0
Test suite present — 14 test file(s) found
14 test file(s) detected (e.g. test_alias.py)
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (3473 chars)
○ 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
190 type-annotated function signatures detected in source
◈ Medium
Multiple Contributors
6.0
Limited contributor diversity
2 unique contributor(s) across 31 commits in AmritaBot/AmritaSenseTwo distinct contributors found
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
No author email provided
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository AmritaBot/AmritaSense appears legitimate
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 amrita-sense
Create a real-time event monitoring and notification system using the 'amrita-sense' Python package. This system will be designed to monitor various events from different sources and trigger notifications based on specific conditions. Here’s a detailed breakdown of what your application should do: 1. **Event Sources**: Define multiple event sources such as logs, network traffic, sensor data, etc., which will feed into your system. Each source should have a unique identifier. 2. **Event Processing**: Utilize 'amrita-sense' to process these events in real-time. The package should be able to filter, transform, and route events based on defined rules. 3. **Condition-Based Notifications**: Implement logic within 'amrita-sense' workflows to send notifications (e.g., via email, SMS, or push notifications) when certain conditions are met. For example, if a server log shows a critical error, the system should notify the appropriate team immediately. 4. **Dashboard Interface**: Develop a simple web-based dashboard using Flask or Django to visualize the incoming events and the status of each event source. Users should be able to see real-time updates and historical data. 5. **Configuration Management**: Allow users to configure event sources, processing rules, and notification triggers through the dashboard. This should include adding new event types, modifying existing ones, and setting up custom workflows. 6. **Scalability and Performance**: Ensure your system can handle a high volume of events without significant performance degradation. Use 'amrita-sense' to manage load balancing and scaling of event processing tasks. 7. **Security Measures**: Implement basic security measures such as user authentication and authorization for accessing the dashboard and configuring event sources. 8. **Documentation and Testing**: Provide comprehensive documentation detailing how to set up and use the system, along with unit tests for critical components. By following these steps, you'll create a robust, scalable, and secure real-time event monitoring and notification system utilizing the advanced capabilities of 'amrita-sense'.
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