airvo

v0.9.1 suspicious
6.0
Medium Risk

Your local AI coding copilot — any model, any provider, zero cloud.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits medium risk due to network calls to potentially unrelated URLs and incomplete metadata, raising concerns about its legitimacy and safety.

  • network risk due to external URL calls
  • incomplete metadata
Per-check LLM notes
  • Network: The package makes external network calls to URLs that seem unrelated to its name and purpose, which may indicate unexpected behavior or potential data exfiltration.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of malicious intent related to stealing credentials.
  • Metadata: The package contains non-secure links and lacks author details, suggesting potential unreliability.

📦 Package Quality Overall: Low (3.8/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 1 test file(s) detected (e.g. test_multi.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (37210 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

  • 127 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 9.0

Found 6 network call pattern(s)

  • s.""" try: with urllib.request.urlopen(f"{base_url}/api/tags", timeout=2) as r:
  • "] try: req = urllib.request.Request( "https://openrouter.ai/api/v1/models",
  • n"}, ) with urllib.request.urlopen(req, timeout=8) as r: raw = json.loads(
  • i/ps" try: with urllib.request.urlopen(url, timeout=2) as resp: data = json.lo
  • () try: req = urllib.request.Request( url, data=payload,
  • ST", ) with urllib.request.urlopen(req, timeout=5): pass logger.i
✓ 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 score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://127.0.0.1:8765/docs`
✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ 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 airvo 
Develop a Python-based desktop application named 'CodeMate' using the 'airvo' package, which acts as your local AI coding assistant. This application should provide real-time suggestions and corrections to the code you're writing, leveraging AI models from various providers without needing an internet connection. CodeMate will support multiple programming languages including Python, JavaScript, and Java.

Steps to create the application:
1. Install the 'airvo' package if not already installed.
2. Set up a basic GUI using a library such as PyQt or Tkinter.
3. Integrate the 'airvo' package to load AI models locally for different programming languages.
4. Implement a feature where the application reads the code being written in real-time and provides suggestions or corrections through the loaded AI models.
5. Add a feature that highlights potential bugs or inefficiencies in the code as the user types.
6. Include an option to save the current session of coding with suggestions and corrections provided by the AI.
7. Ensure the application can handle multiple files and projects at once.
8. Test the application thoroughly with different code snippets in various programming languages to ensure accuracy and efficiency.

Features:
- Real-time code suggestion and correction
- Local AI model integration without internet dependency
- Multiple language support
- Bug and inefficiency highlighting
- Session saving with AI feedback
- Multi-file and multi-project handling

Utilizing the 'airvo' package: The 'airvo' package will be crucial for loading and utilizing AI models locally. These models will be trained on specific programming languages and will provide context-aware suggestions and corrections. The package simplifies the process of integrating these models into the application, ensuring that the AI assistance is available offline and does not require constant internet connectivity.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!