awslabs.aws-iac-mcp-server

v1.0.19 suspicious
7.0
High Risk

An Infrastructure as Code MCP server that provides CloudFormation template validation, compliance checking, and deployment troubleshooting capabilities.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits a high credential risk due to suspicious file access patterns, while other risks remain low. This behavior raises concerns about potential credential harvesting.

  • High credential risk due to inclusion of '../../etc/passwd' in the regions list.
  • Low network and shell execution risks.
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external API interactions.
  • Shell: No shell execution patterns detected, indicating the package likely does not execute system commands.
  • Obfuscation: The observed pattern is a common technique to extend a package's import path and does not necessarily indicate malicious activity.
  • Credentials: The inclusion of '../../etc/passwd' in the regions list is highly suspicious and likely indicates an attempt to harvest system credentials.
  • Metadata: The author has only one package, which may indicate a new or less active account but does not necessarily suggest malintent.

📦 Package Quality Overall: Medium (6.6/10)

✦ High Test Suite 9.0

Test suite present — 15 test file(s) found

  • Test runner config found: pyproject.toml
  • 15 test file(s) detected (e.g. __init__.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://awslabs.github.io/mcp/servers/aws-iac-mcp-server/
  • Detailed PyPI description (13798 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

  • 19 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 42 unique contributor(s) across 100 commits in awslabs/mcp
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

  • amespace packages. __path__ = __import__('pkgutil').extend_path(__path__, __name__) # Copyright Amazon.com, In
✓ Shell / Subprocess Execution

No shell execution patterns detected

⚠ Credential Harvesting score 2.5

Found 1 credential access pattern(s)

  • , regions=['us-east-1', '../../etc/passwd']) assert isinstance(result, dict) def test_sq
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: amazon.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository awslabs/mcp appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Amazon Web Services" 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 awslabs.aws-iac-mcp-server 
Develop a comprehensive tool named 'CloudFormation Validator' using Python and the 'awslabs.aws-iac-mcp-server' package. This tool aims to simplify the process of validating, ensuring compliance, and troubleshooting issues related to AWS CloudFormation templates. The application should provide a user-friendly interface for uploading CloudFormation templates, validating them against AWS standards, checking their compliance with organizational policies, and offering insights into potential deployment issues.

Key Features:
1. Template Upload: Allow users to upload their CloudFormation templates via a simple command-line interface or a web-based frontend.
2. Validation: Use the 'awslabs.aws-iac-mcp-server' package to validate the uploaded templates, ensuring they adhere to AWS best practices and syntax rules.
3. Compliance Checking: Integrate the compliance checking feature of the package to verify if the templates comply with specified organizational policies and security guidelines.
4. Troubleshooting: Implement the deployment troubleshooting capabilities provided by the package to identify and suggest solutions for common deployment issues within the templates.
5. Reporting: Generate detailed reports summarizing the validation results, compliance status, and troubleshooting suggestions for each uploaded template.
6. User Interface: Design both a CLI and a basic web interface for ease of use.

The 'awslabs.aws-iac-mcp-server' package will be utilized extensively throughout the development process. It will serve as the backbone for all validation, compliance checking, and troubleshooting functionalities. Developers should explore the package documentation thoroughly to understand its APIs and integrate them effectively into the application. Additionally, consider implementing error handling mechanisms to ensure smooth operation even when dealing with complex or erroneous templates.

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