argon-architecture-scanner

v0.9.2 suspicious
6.0
Medium Risk

Pre-1.0 token-budgeted architecture context engine for AI coding assistants.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risks due to its network and shell execution capabilities, though it lacks malicious intent indicators like obfuscation or credential harvesting.

  • High network risk due to external service calls
  • High shell risk due to potential unauthorized pip command executions
Per-check LLM notes
  • Network: The package makes network calls to an external service, which could be used for unauthorized data transmission.
  • Shell: The package attempts to execute pip commands, potentially altering the system's software environment without user consent.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: Low activity and lack of classifiers suggest low effort, but no immediate signs of malice.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 5 test file(s) found

  • 5 test file(s) detected (e.g. test_bench_and_laravel.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (6137 chars)
○ 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

  • 189 type-annotated function signatures detected in source
○ 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 score 3.0

Found 2 network call pattern(s)

  • }).encode() req = urllib.request.Request( 'http://localhost:11434/api/embed',
  • ) with urllib.request.urlopen(req, timeout=30) as resp: data = jso
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • sys.stderr) try: subprocess.check_call( [sys.executable, "-m", "pip", "install", "--qui
✓ 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 4.0

2 maintainer concern(s) found

  • Author "Dante7u7r" 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 argon-architecture-scanner 
Develop a Python-based application named 'ArchitecturalAnalyzer' that leverages the 'argon-architecture-scanner' package to analyze and visualize software architecture patterns within existing codebases. This tool aims to assist developers in understanding complex systems by providing insights into their architectural structure. Here’s a detailed breakdown of what your application should accomplish:

1. **Setup and Configuration**: Begin by installing the required dependencies including 'argon-architecture-scanner'. Ensure that the application can read configuration files where users can specify paths to code repositories or directories.

2. **Codebase Analysis**: Utilize 'argon-architecture-scanner' to scan the specified codebase and extract relevant architecture information such as layers, components, and their interdependencies. The tool should be capable of handling different programming languages and frameworks.

3. **Visualization**: Implement a feature that generates visual representations of the extracted architecture data. These could be in the form of graphs or diagrams, helping users to easily understand the relationships between various parts of the system.

4. **Report Generation**: Develop a functionality that creates detailed reports summarizing the findings from the code analysis. Reports should include insights on architectural patterns, potential issues, and recommendations for improvement.

5. **User Interface**: Optionally, design a simple command-line interface (CLI) or a basic web interface for interacting with the application. This would allow users to input paths, view results, and generate reports without needing extensive technical knowledge.

6. **Integration with CI/CD Pipelines**: Explore ways to integrate ArchitecturalAnalyzer into Continuous Integration/Continuous Deployment (CI/CD) pipelines, enabling automated architectural checks during development cycles.

**Features to Consider**:
- Support for multiple programming languages and frameworks.
- Customizable visualization options (e.g., graph layout, color schemes).
- Exporting reports in various formats (PDF, HTML, etc.).
- Real-time feedback during code analysis.

By following these steps and incorporating these features, you will create a valuable tool that enhances developers' ability to maintain and improve the quality of software architectures.

💬 Discussion Feed

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