🤖 AI Analysis

Final verdict: SAFE

The package has minimal risks associated with network, shell execution, obfuscation, and credential handling. The metadata risk score is slightly elevated due to suspicious non-HTTPS links and limited author activity, but there is no concrete evidence of malicious intent.

Suspicious non-HTTPS links in metadata
Limited author activity

Per-check LLM notes

Network: No network calls suggest the package does not engage in external communications, which is normal unless specific network interactions are expected.
Shell: No shell executions indicate that the package does not attempt to run system commands, reducing the risk of potential malicious activities.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets and credentials.
Metadata: Suspicious non-HTTPS links and an author with limited activity suggest potential risk.

🔬 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 score 4.0

Found 2 suspicious link(s) on the package page

Non-HTTPS external link: http://192.168.1.10:8000
Non-HTTPS external link: http://192.168.1.11:8000

⚠ 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 PyObservability

Create a fully functional mini-application called 'PyNinjaMonitor' that leverages the PyObservability package to provide real-time monitoring and debugging capabilities for a simple web scraping task. This application will be designed to scrape data from a specified website, process it, and then visualize the performance metrics such as request times, error rates, and resource usage through a user-friendly dashboard provided by PyObservability.

Steps:
1. Set up a basic Flask web server to act as the backend of your application. This server will handle incoming requests to start the web scraping task.
2. Integrate the PyObservability package into your Flask application to monitor the backend processes. Use its logging capabilities to track the execution of the web scraping tasks.
3. Implement a simple web scraper using Python libraries like BeautifulSoup or Scrapy. Ensure that this scraper fetches data from a configurable URL passed via the Flask API.
4. Utilize PyObservability's visualization tools to create a dashboard within the Flask app that displays real-time performance metrics of the scraping operation. Metrics should include response times, error rates, and CPU/RAM usage.
5. Extend the application by adding an option for users to schedule periodic scrapes via the Flask API. Monitor these scheduled tasks on the dashboard as well.
6. Finally, enhance the application by allowing users to input custom Python scripts through the Flask API for more complex data processing after scraping. Monitor the execution of these scripts in real-time using PyObservability.

Features:
- Configurable URL for web scraping
- Real-time dashboard displaying scraping performance metrics
- Option to schedule periodic scraping tasks
- Ability to execute custom post-processing scripts
- Detailed logs and alerts for errors during scraping or script execution

The goal is to demonstrate how PyObservability can be integrated seamlessly into a Python application to enhance observability and manage complex workflows effectively.