agi-page-queue-health

v2026.5.31 suspicious
4.0
Medium Risk

AGILAB page bundle for queue health and resilience evidence.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has minimal risks in terms of network calls, shell execution, and obfuscation. However, the metadata risk score suggests low maintenance, raising suspicion about its integrity.

  • Low metadata maintenance
  • No direct risks identified but low maintenance is concerning
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require internet access.
  • 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 package shows low maintenance and effort signs which may indicate potential risk.

📦 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 5.0

Some documentation present

  • Documentation URL: "Documentation" -> https://thalesgroup.github.io/agilab
○ 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

  • 6 type-annotated function signatures (partial)
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 5 unique contributor(s) across 69 commits in ThalesGroup/agilab
  • Active community — 5 or more distinct contributors

🔬 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

Repository ThalesGroup/agilab appears legitimate

⚠ 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 agi-page-queue-health 
Create a web-based monitoring tool using Python and the 'agi-page-queue-health' package. This tool will allow users to monitor the health and resilience of their queue systems in real-time. The application should have the following features:

1. **Queue Status Monitoring**: Display the current status of multiple queues, including their processing speed, latency, and any errors encountered.
2. **Resilience Analysis**: Provide insights into how well the queue system handles unexpected spikes in traffic or failures.
3. **Health Reports**: Generate periodic reports summarizing the performance of each queue over time.
4. **User Management**: Allow administrators to add, remove, and manage different user roles within the application.
5. **Alert System**: Implement an alert system that notifies users via email or SMS when a queue's health falls below a certain threshold.

To achieve these functionalities, utilize the 'agi-page-queue-health' package to gather data about the queue's health and resilience. Integrate this data into your application's backend using Flask or Django, and display it through a React frontend. Ensure the application is user-friendly and provides actionable insights to improve queue management.

💬 Discussion Feed

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