api-tracker

v0.1 safe
3.0
Low Risk

API tracking system

🤖 AI Analysis

Final verdict: SAFE

The package has minimal risks across all categories with no network calls, shell executions, or obfuscation detected. While there are some concerns about metadata quality, these alone do not indicate malicious intent.

  • Low network and shell risk
  • No obfuscation or credential harvesting detected
  • Metadata suggests low effort but no malicious indicators
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package is expected to make API calls.
  • Shell: No shell execution detected, reducing the likelihood of malicious activities.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows some signs of low effort and possibly a new maintainer, but lacks clear indicators of malicious intent.

📦 Package Quality Overall: Low (1.2/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
○ Low Documentation 1.0

No documentation detected

  • No documentation URL, doc files, or meaningful description found
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
○ 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

  • Only one version has ever been released — brand new package
  • Author "Pulkit" 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 api-tracker 
Create a comprehensive API monitoring tool using the 'api-tracker' package. This tool will serve as a dashboard for developers to monitor the performance and health of their APIs in real-time. The application should include the following core functionalities:

1. **API Endpoint Tracking**: Allow users to input multiple API endpoints and track their status, response time, and success/failure rates.
2. **Real-Time Alerts**: Implement a feature that sends notifications via email or SMS when an API endpoint experiences prolonged downtime or unusually high error rates.
3. **Historical Data Analysis**: Provide visualizations and reports based on historical data to help identify trends and potential issues over time.
4. **Customizable Thresholds**: Enable users to set custom thresholds for alerting based on their specific needs.
5. **User Authentication**: Secure the application with user authentication to ensure only authorized personnel can access the monitoring data.
6. **Integration Capabilities**: Allow easy integration with other tools or services such as Slack, Jira, or any other ticketing system for better incident management.

To achieve these functionalities, you'll need to utilize the 'api-tracker' package effectively. Start by exploring its documentation to understand how it handles API requests, tracks responses, and manages data. Use its core features to implement the real-time monitoring and alerting system. Additionally, consider leveraging external libraries for the visualization and reporting components, as well as for sending out alerts through various channels. Remember to design the application with scalability in mind, ensuring it can handle multiple API endpoints and large volumes of data efficiently.

💬 Discussion Feed

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