aigaze

v0.1.0 suspicious
4.0
Medium Risk

Audit AI agent actions from transcript files

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package aigaze v0.1.0 has low risks in terms of network, shell, obfuscation, and credential activities. However, its metadata risk score is elevated due to the absence of a GitHub repository and inactive maintenance, suggesting potential suspicion.

  • Lack of a GitHub repository and inactive maintainer
  • Low risk in direct malicious activities
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires network functionality.
  • Shell: No shell execution patterns detected, indicating no immediate signs of malicious activity.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package seems suspicious due to the lack of a GitHub repository and the maintainer's inactivity, but there's no concrete evidence of malice.

📦 Package Quality Overall: Low (3.8/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 2 test file(s) detected (e.g. test_engine.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (1014 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

  • 26 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

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

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

  • Only one version has ever been released — brand new package
  • Author "aigaze-sec" 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 aigaze 
Create a fully functional mini-application called 'AIWatch' using the Python package 'aigaze'. This application will serve as a tool for auditing the actions of AI agents based on their interaction transcripts. Here are the steps and features you should consider implementing:

1. **Setup and Configuration**: Start by installing the necessary packages including 'aigaze'. Ensure that your application allows users to configure which AI agent's transcript files they want to audit.
2. **File Parsing**: Implement functionality within 'AIWatch' to parse through the transcript files provided by the user. These files could be in various formats like .txt, .json, etc., and should contain interactions between users and the AI agent.
3. **Action Extraction**: Utilize the core functionalities of 'aigaze' to extract actions performed by the AI agent from these transcripts. Actions could range from providing information, answering questions, making recommendations, etc.
4. **Audit Analysis**: Develop an audit analysis feature that evaluates the extracted actions against predefined criteria such as correctness, relevance, and efficiency. Users should be able to customize these criteria based on their specific needs.
5. **Visualization and Reporting**: Integrate visualization tools to display the audit results in an easy-to-understand format. Additionally, generate comprehensive reports summarizing the audit findings.
6. **User Interface**: Design a simple yet effective user interface for 'AIWatch', allowing users to upload files, view audit results, and customize audit parameters easily.
7. **Security and Privacy**: Ensure that all data handling complies with relevant security and privacy standards, especially concerning user interaction transcripts.

By following these steps and incorporating these features, 'AIWatch' will become a valuable tool for anyone looking to monitor and improve the performance of AI agents through systematic audits.

💬 Discussion Feed

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