🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows no immediate signs of malicious activity but raises concerns due to its recent creation and lack of maintainer details, suggesting potential risks that warrant further investigation.

New package with no maintainer information
Lack of historical data to verify package integrity

Per-check LLM notes

Network: No network calls suggest normal behavior for most utility packages.
Shell: No shell executions indicate the package does not execute external commands.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
Credentials: No credential harvesting patterns detected, indicating secure handling of secrets and credentials.
Metadata: The package is suspicious due to its newness and lack of maintainer information.

📦 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

78 type-annotated function signatures detected in source

✦ 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 10.0

5 maintainer concern(s) found

Only one version has ever been released — brand new package
Package is very new: uploaded 3 day(s) ago
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-promotion-gate

Create a mini-application named 'PromotionGateReviewTool' using Python that leverages the 'agi-page-promotion-gate' package. This tool will streamline the process of reviewing and promoting pages within the AGILAB framework. Your task involves designing a user-friendly interface where users can input details about a page they wish to promote, including metrics like page views, engagement rates, and conversion rates. The app should also allow for uploading evidence files such as screenshots or reports that support the promotion request.

The core functionalities of your application should include:
- A form to collect page promotion data from the user.
- Integration with the 'agi-page-promotion-gate' package to perform automated checks based on predefined criteria (e.g., minimum page views, engagement thresholds).
- A feature to upload and manage evidence files associated with the promotion request.
- An approval/disapproval mechanism based on the outcome of the automated checks and manual review.
- Optionally, implement a notification system that alerts relevant stakeholders when a new promotion request is submitted or when a decision has been made.

Your application should be designed with scalability in mind, allowing for easy updates to the criteria for promotion and the addition of new types of evidence without significant code changes. Additionally, ensure that the user experience is smooth and intuitive, providing clear feedback at each step of the process.