INFRA-COMPASS

v0.19.0 suspicious
4.0
Medium Risk

INFRA-COMPASS is a tool that leverages Large Language Models (LLMs) to create and maintain an inventory of state and local codes and ordinances applicable to energy infrastructure.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows very low risks in terms of network, shell, and obfuscation activities, with no signs of malicious behavior. However, the incomplete author metadata raises some suspicion.

  • Incomplete author metadata
  • New or inactive author
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package's functionality requires external communication.
  • Shell: No shell execution patterns detected, indicating no immediate risk of command execution from the package.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author's information is incomplete and they appear to be new or inactive, raising some suspicion but not definitive proof of malicious intent.

🔬 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

Email domain looks legitimate: nlr.gov>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository NatLabRockies/COMPASS appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" 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 INFRA-COMPASS 
Your task is to develop a web-based mini-application called 'CodeQuery' using Python's INFRA-COMPASS package. This application will serve as a user-friendly interface for querying and managing state and local codes and ordinances related to energy infrastructure. CodeQuery should allow users to search for specific codes by keyword, location, or category, and provide detailed information about each code, including its applicability, enforcement details, and relevant amendments.

Core Features:
1. User Authentication: Implement basic login functionality to ensure only registered users can access the full set of features.
2. Search Functionality: Users should be able to search for codes based on various criteria such as keywords, geographic location, and type of ordinance.
3. Detailed View: Each code entry should have a detailed view providing comprehensive information about the ordinance, including any amendments or updates.
4. Inventory Management: Administrators should have the ability to add, edit, and remove codes from the inventory.
5. Notifications: Users should receive email notifications when new codes are added or existing ones are updated, affecting their area of interest.

Utilizing INFRA-COMPASS:
- Use INFRA-COMPASS to integrate with an LLM to dynamically update the code inventory based on the latest data available online or through API calls.
- Leverage INFRA-COMPASS's capabilities to automatically categorize and tag codes based on their relevance to different types of energy infrastructure projects.
- Employ INFRA-COMPASS for natural language processing tasks to improve the accuracy of searches and to enhance the user experience by providing contextually relevant information.

Your goal is to create a fully functional prototype of CodeQuery that demonstrates these core features while effectively utilizing the INFRA-COMPASS package.