🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of malicious activities such as network risks, shell risks, obfuscation, or credential theft. However, it has a moderate metadata risk due to its newness and lack of community support.

No network calls detected
No shell execution patterns
Low obfuscation risk
No credential harvesting patterns
Minimal community activity

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external API interactions.
Shell: No shell execution patterns detected, indicating no immediate risk of command injection or similar attacks.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
Credentials: No credential harvesting patterns detected, suggesting no immediate threat to secrets or credentials.
Metadata: The package is new with minimal activity and no established community support.

🔬 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 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

Only one version has ever been released — brand new package
Author "David Mosiah" 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 agent-seo-engine

Create a Python-based web application named 'SEOAnalyzer' that leverages the 'agent-seo-engine' package to analyze and optimize website content for better search engine visibility. This application will serve as a tool for digital marketers and web developers to enhance their SEO strategies by identifying potential improvements in website content and structure.

Step-by-Step Requirements:
1. **Setup Environment**: Install Python and necessary packages including 'agent-seo-engine'.
2. **User Interface**: Develop a simple, intuitive web interface using Flask or Django, where users can input URLs of websites they want to analyze.
3. **Analysis Engine**: Utilize 'agent-seo-engine' to perform SEO analysis on the provided URL. The analysis should include but not be limited to keyword optimization, meta tag evaluation, and page load speed.
4. **Report Generation**: After the analysis, generate a comprehensive report detailing the findings and suggestions for improvement. This report should be both viewable within the app and downloadable as a PDF.
5. **Optional Features**:
- Implement a dashboard to track multiple sites over time.
- Add a feature to compare SEO metrics between different websites.
- Incorporate machine learning models to predict future SEO trends based on historical data.
6. **Deployment**: Prepare the application for deployment on platforms like Heroku or AWS, ensuring it can handle multiple concurrent users efficiently.

How 'agent-seo-engine' is Utilized:
- Use 'agent-seo-engine' to crawl the target website and extract relevant SEO data.
- Apply its analytical capabilities to assess the quality of content and identify opportunities for improvement.
- Leverage any additional features provided by 'agent-seo-engine', such as command-line interface options or integration with a monitoring control plane (MCP), to enhance the functionality and user experience of 'SEOAnalyzer'.