agentclaimguard

v0.4.1 suspicious
5.0
Medium Risk

A framework-agnostic evidence gate for LLM agent claims.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risk in terms of network and shell activities but has a high metadata risk due to recent rapid commit activity and a new maintainer account.

  • Recent rapid commit activity
  • New maintainer account
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communication.
  • Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
  • Metadata: Recent rapid commit activity and a new maintainer account raise suspicion.

🔬 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 score 2.5

Git history flags: All 33 commits happened within 24 hours

  • All 33 commits happened within 24 hours
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Hao Peng" 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 agentclaimguard
Create a mini-application named 'ClaimVerifier' that utilizes the 'agentclaimguard' package to verify the accuracy of claims made by an AI agent in real-time. This application will serve as a bridge between users and AI agents, ensuring that any information provided by the agent is backed by credible evidence. Here's how you can structure your project:

1. **Project Setup**: Start by setting up a virtual environment and installing the 'agentclaimguard' package along with any other necessary dependencies.
2. **Application Design**: Design the application to have two main components - an interface for users to interact with the AI agent and a backend system that leverages 'agentclaimguard' to verify claims.
3. **User Interface**: Develop a simple but intuitive user interface where users can input queries to the AI agent and receive responses. Ensure the UI clearly indicates when a claim is being verified.
4. **Integration with AI Agent**: Integrate an existing AI agent API into your application. This could be an open-source model like GPT-3 or any other compatible service.
5. **Verification Process**: Use 'agentclaimguard' to automatically verify each claim made by the AI agent against reliable sources. Implement a mechanism within the package to specify which types of claims need verification and how they should be validated.
6. **Feedback Loop**: Implement a feedback loop where if a claim cannot be verified, the application requests additional clarification from the AI agent or suggests alternative sources of information.
7. **Reporting**: Provide a reporting feature that allows users to review past interactions, including the original claim, verification status, and any supporting evidence.
8. **Security and Privacy**: Ensure all user interactions and data handling comply with relevant privacy regulations. Utilize secure methods for storing and transmitting data.
9. **Testing and Validation**: Rigorously test the application to ensure it accurately verifies claims and handles various types of inputs effectively.
10. **Documentation**: Write comprehensive documentation explaining how to use the application, how 'agentclaimguard' is integrated, and any best practices for maintaining the application over time.

Suggested Features:
- Real-time verification notifications
- Ability to customize verification rules based on context
- Detailed logging of verification processes for auditing purposes
- Integration with multiple AI agent APIs for flexibility
- User-friendly dashboard for reviewing historical interactions

This project aims to demonstrate the practical application of 'agentclaimguard' in enhancing trust and reliability in AI-agent communications.

💬 Discussion Feed

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