automas-notification-system

v0.0.4 safe
3.0
Low Risk

Notification system channel

🤖 AI Analysis

Final verdict: SAFE

The package is deemed safe with no indications of malicious activities. However, there are some metadata concerns that warrant further investigation.

  • Low network, shell, obfuscation, and credential risks.
  • Metadata shows some red flags but lacks clear evidence of malice.
Per-check LLM notes
  • Network: No network calls suggest the package does not engage in external communications which is normal unless specific features require it.
  • Shell: No shell executions indicate the package is not running system commands, which is expected and safe.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets.
  • Metadata: The package shows some red flags but lacks clear evidence of malice or typosquatting.

📦 Package Quality Overall: Low (2.8/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Brief PyPI description (217 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

  • 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

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 short
  • Author "" 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 automas-notification-system 
Create a mini-app called 'AlertMaster' which is designed to manage and send various types of notifications based on user-defined conditions. The app should allow users to set up different notification channels (e.g., email, SMS, push notifications) through the 'automas-notification-system' package and configure rules for when these notifications should be sent out.

Step 1: Setup the Project Environment
- Initialize a new Python project and install the 'automas-notification-system' package along with other necessary dependencies such as Flask for the web interface and SQLAlchemy for database management.

Step 2: Define the Core Features
- Users should be able to create accounts and log in to their AlertMaster dashboard.
- Users can add notification channels they want to receive alerts from (e.g., email, SMS).
- Each channel requires configuration specific to its type (e.g., email address, phone number).
- Users can define alert rules, specifying conditions under which alerts should be triggered (e.g., stock price falls below a certain threshold).

Step 3: Implement the Notification System
- Utilize the 'automas-notification-system' package to handle sending notifications across different channels efficiently.
- Ensure that the system supports scheduling notifications for future times and recurring alerts.
- Implement error handling for failed notifications and retry mechanisms.

Step 4: Enhance User Experience
- Develop a responsive and intuitive UI using HTML/CSS/JavaScript frameworks like Bootstrap.
- Provide real-time feedback to users about the status of their alerts and notifications.
- Allow users to customize the content and format of their notifications.

Step 5: Testing and Deployment
- Thoroughly test the application in a development environment before deploying it to production.
- Ensure all functionalities work as expected and there are no security vulnerabilities.
- Deploy the application to a cloud platform such as AWS or Heroku.

Suggested Additional Features:
- Integration with external APIs for more complex condition checking (e.g., weather alerts).
- Support for multiple languages for international users.
- A mobile app version for receiving notifications on-the-go.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!