apibrasil-requests-monitor

v0.1.0 safe
4.0
Medium Risk

SDK de monitoramento de requests para APIs Flask da APIBrasil

🤖 AI Analysis

Final verdict: SAFE

The package appears to serve its intended purpose of monitoring Flask API requests with low risk indicators. While there are some concerns regarding metadata quality, no concrete evidence suggests malicious intent or supply-chain attack.

  • Low network, shell, obfuscation, and credential risks
  • Potential lack of transparency in metadata
Per-check LLM notes
  • Network: The observed network call pattern is likely legitimate for monitoring and reporting purposes.
  • Shell: No shell execution patterns detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows signs of low effort and potential lack of transparency, raising some suspicion but not definitive evidence of malice.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 5 test file(s) found

  • Test runner config found: pyproject.toml
  • 5 test file(s) detected (e.g. test_client.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (4235 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

  • 22 type-annotated function signatures detected in source
○ 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 score 1.5

Found 1 network call pattern(s)

  • try: response = requests.post( self.endpoint, json=event
✓ 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 8.0

4 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • 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 apibrasil-requests-monitor 
Create a Flask-based web application that monitors API requests using the 'apibrasil-requests-monitor' package. Your goal is to develop a utility that not only tracks but also visualizes the performance of these requests in real-time. Here’s a detailed plan on how to achieve this:

1. **Setup**: Begin by installing the necessary packages including Flask and 'apibrasil-requests-monitor'. Ensure your development environment is set up correctly.

2. **Application Structure**: Design your Flask application to include routes that will simulate different types of API requests (GET, POST, etc.). Each route should utilize 'apibrasil-requests-monitor' to log request details such as timestamp, method, status code, and response time.

3. **Monitoring Integration**: Integrate 'apibrasil-requests-monitor' into your Flask app to automatically capture all incoming requests and store them in a database or file for later analysis.

4. **Real-Time Dashboard**: Develop a real-time dashboard within your Flask app that displays key metrics about the API requests. This dashboard should update dynamically to reflect the most recent data.

5. **Visualization**: Implement graphs and charts using libraries like Plotly or Matplotlib to visualize the request patterns over time. For example, show the number of requests per minute, average response times, and error rates.

6. **Alerts & Notifications**: Add functionality to send alerts via email or SMS when certain thresholds are breached, such as high error rates or unusually long response times.

7. **Security Measures**: Ensure that sensitive information is not logged or displayed. Use appropriate security measures to protect the data collected from the API requests.

8. **Testing & Validation**: Thoroughly test your application under various conditions to ensure it behaves as expected. Validate the accuracy of the monitoring and visualization components.

9. **Documentation**: Write comprehensive documentation detailing how to install, configure, and use your application. Include examples of how to extend its functionality.

Your final deliverable should be a fully functional Flask application that demonstrates the capabilities of 'apibrasil-requests-monitor', providing insights into API performance and usage patterns.

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