aiotieba

v4.7.1 safe
3.0
Low Risk

Asynchronous I/O Client for Baidu Tieba

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risk indicators with no network calls, shell executions, obfuscations, or credential harvesting attempts detected. However, the incomplete maintainer's author information slightly increases suspicion.

  • Incomplete maintainer's author information
  • No detected malicious activities
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communication.
  • Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer's author information is incomplete, suggesting a potentially less established or suspicious account.

📦 Package Quality Overall: Low (4.6/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://aiotieba.cc/
  • Detailed PyPI description (2915 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 50 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 100 commits in lumina37/aiotieba
  • 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

Repository lumina37/aiotieba appears legitimate

⚠ 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 aiotieba 
Create a real-time monitoring tool for Baidu Tieba using the 'aiotieba' package. This tool will allow users to track specific Tieba forums for new threads and replies. Here are the steps and features to include:

1. **Setup**: Start by installing the necessary packages, including 'aiotieba'. Ensure you have Python 3.7+ installed.
2. **User Interface**: Develop a simple command-line interface (CLI) for the user to interact with the tool. The CLI should allow users to input the Tieba forum they wish to monitor and keywords to filter threads or replies.
3. **Real-Time Monitoring**: Use 'aiotieba' to asynchronously fetch new threads and replies from the specified Tieba forum. Implement a mechanism to continuously check for updates without blocking the main thread.
4. **Notification System**: Whenever a new thread or reply matching the user-defined criteria is detected, send a notification to the user via email, SMS, or push notification through a service like Twilio or Firebase.
5. **Database Storage**: Store the monitored data (threads, replies, timestamps) in a local SQLite database for later analysis or reporting purposes.
6. **Configuration Management**: Allow users to save their monitoring preferences and settings in a configuration file (JSON/YAML) so they don't need to re-enter them each time they run the tool.
7. **Error Handling**: Implement robust error handling to manage potential issues such as network errors, API rate limits, or unexpected responses from 'aiotieba'.
8. **Logging**: Include logging capabilities to record important events, such as successful notifications sent, errors encountered, and periodic status updates of the monitoring process.
9. **Security Measures**: If your tool involves sensitive information (like credentials for sending notifications), ensure it is stored securely and not hard-coded into the source code.

By completing these steps, you'll create a powerful, real-time monitoring tool for Baidu Tieba that leverages the asynchronous capabilities of the 'aiotieba' package.

💬 Discussion Feed

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