🤖 AI Analysis

Final verdict: SAFE

The package is deemed safe due to low risks across all technical checks. However, there is some concern about its metadata, suggesting it may be new or less active.

Low risk scores across network, shell, obfuscation, and credential risks.
Metadata suggests potential inactivity or novelty of the package.

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires internet access for its functionality.
Shell: No shell execution detected, indicating the package does not attempt to execute external commands.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows signs of being potentially new or inactive with minimal maintainer history and low repository engagement.

📦 Package Quality Overall: Medium (5.6/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

Test runner config found: pyproject.toml

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (3284 chars)

○ Low Contributing Guide 4.0

No contributing guide or governance files found

Development Status classifier >= Beta

◈ Medium Type Annotations 7.0

Partial type annotation coverage

Classifier: Typing :: Typed
Type checker (mypy / pyright / pytype) referenced in project
6 type-annotated function signatures (partial)

◈ Medium Multiple Contributors 6.0

Limited contributor diversity

2 unique contributor(s) across 12 commits in adalekin/approck-messaging
Two 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

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

Repository has zero stars and zero forks

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author name is missing or very short
Author "" 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 approck-messaging

Create a mini-application that serves as a simple messaging service using the 'approck-messaging' Python package. This application will allow users to send and receive messages through a Telegram-like interface, utilizing Pydantic for message validation and FastStream/Redis for message transport. Here’s a step-by-step guide on how to develop this application:

1. **Project Setup**: Start by setting up a new Python environment. Install the required packages including 'approck-messaging', 'pydantic', 'fastapi', and 'redis'.
2. **Define Message Models**: Use Pydantic to define the structure of your messages. Consider fields such as sender ID, recipient ID, message content, timestamp, and message status.
3. **Message Validation**: Implement validation logic to ensure all incoming messages adhere to the defined schema. This ensures data integrity and consistency across the system.
4. **Transport Layer Setup**: Configure FastStream/Redis to handle the message transport layer. Set up endpoints for sending and receiving messages, ensuring that messages are correctly routed based on their destination.
5. **User Interface**: Develop a basic user interface where users can input messages and view their inbox. This could be a web-based UI using FastAPI or a simple command-line interface.
6. **Real-Time Messaging**: Utilize Redis Pub/Sub capabilities to enable real-time messaging between users. Ensure that messages are delivered promptly and reliably.
7. **Error Handling and Logging**: Implement robust error handling and logging mechanisms to capture and report issues effectively. This includes handling network errors, message delivery failures, and other potential issues.
8. **Security Measures**: Incorporate basic security measures such as user authentication and message encryption to protect user data.
9. **Testing**: Conduct thorough testing to ensure all components work together seamlessly. Include unit tests for message validation, integration tests for the transport layer, and end-to-end tests for the complete messaging flow.
10. **Deployment**: Prepare the application for deployment. This might involve setting up a production-ready environment, configuring monitoring and alerting, and ensuring scalability.

By following these steps, you'll create a functional and efficient messaging service that leverages the powerful features of the 'approck-messaging' package.