aigatekeeper

v0.2.1 suspicious
6.0
Medium Risk

Policy gateway for Google Workspace APIs with MCP server integration

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits several risky behaviors including elevated privilege operations and possible code obfuscation, which raises concerns about its integrity and intended use.

  • High shell risk due to sudo and tee commands
  • Possible code obfuscation through dynamic imports and string manipulations
Per-check LLM notes
  • Network: The presence of network calls is somewhat expected for an agent or gatekeeper service, but specific endpoints and purposes should be verified.
  • Shell: Use of sudo and tee commands suggests potential for elevated privileges operations which may indicate unexpected behavior or risk.
  • Obfuscation: The code uses dynamic imports and string manipulations which could be an attempt to obfuscate the code, but without further context, it's hard to determine malicious intent.
  • Credentials: No direct signs of credential harvesting are present in the provided snippets.
  • Metadata: Suspicious due to non-secure external link and lack of community engagement, but insufficient evidence for high risk.

📦 Package Quality Overall: Medium (6.2/10)

✦ High Test Suite 9.0

Test suite present — 13 test file(s) found

  • Test runner config found: conftest.py
  • Test runner config found: pyproject.toml
  • 13 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (22658 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 68 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 100 commits in brimdor/gatekeeper
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

  • try: with httpx.Client(timeout=30) as client: # Device code endpoin
  • try: with httpx.Client(timeout=30) as client: token_response =
  • try: async with httpx.AsyncClient() as client: if route.method == "GET":
⚠ Code Obfuscation score 10.0

Found 6 obfuscation pattern(s)

  • nsure_default_key() gv = __import__("gatekeeper").__version__ logger.info(f"Gatekeeper v{gv} ready on {se
  • integration", version=__import__("gatekeeper").__version__, lifespan=lifespan, ) # CORS m
  • n {"status": "ok", "version": __import__("gatekeeper").__version__} # API routes api_router = create_api_
  • print(f" Version: {__import__('gatekeeper').__version__}") print(f" Host: {settings.host}"
  • pathlib import Path logger = __import__("logging").getLogger(__name__) # ------------------------------------
  • k.last_used_at = __import__("datetime").datetime.now( __import__("datetime"
⚠ Shell / Subprocess Execution score 4.0

Found 2 shell execution pattern(s)

  • urn the result.""" return subprocess.run(cmd, check=check, capture_output=True, text=True) def _sys
  • stemd/system result = subprocess.run( ["sudo", "tee", str(unit_path)], in
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

⚠ Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://127.0.0.1:8080
⚠ 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 "Brimdor" 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 aigatekeeper 
Develop a mini-application named 'SecureAccess' that leverages the 'aigatekeeper' package to manage access policies for various Google Workspace APIs, integrating seamlessly with an MCP (Management Control Panel) server. This application will serve as a policy enforcement layer, ensuring that only authorized users can access specific Google Workspace services based on predefined rules and conditions. Here’s a detailed breakdown of the project requirements:

1. **User Authentication**: Integrate Google Workspace OAuth2 authentication to allow users to log in securely.
2. **Policy Management**: Use 'aigatekeeper' to define and manage access policies. Policies should include criteria such as user roles, API endpoints, and time-based restrictions.
3. **MCP Integration**: Ensure the application can communicate with an MCP server to fetch and apply the latest policy configurations dynamically.
4. **Audit Logs**: Implement logging functionality to track access attempts and violations of policies for auditing purposes.
5. **User Interface**: Develop a simple web interface where administrators can view current policies, manage user roles, and monitor access logs.
6. **Security Measures**: Apply best practices for securing data transmission and storage, including encryption for sensitive information.

To utilize the 'aigatekeeper' package effectively, you should:
- Initialize the policy enforcement mechanism using 'aigatekeeper', setting up the connection to the MCP server.
- Define custom policy rules that align with your application's security requirements.
- Handle exceptions and errors gracefully, providing informative messages to both administrators and end-users.
- Regularly update policies from the MCP server to ensure compliance with changing security needs.

This project aims to demonstrate the practical use of 'aigatekeeper' in real-world scenarios, emphasizing its role in enhancing the security and management of Google Workspace API access.

💬 Discussion Feed

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