aport-agent-guardrails-langchain

v1.0.29 suspicious
4.0
Medium Risk

APort Agent Guardrail for LangChain/LangGraph — AsyncCallbackHandler for AI agent tool calls

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows minimal risks in terms of network usage, shell execution, and obfuscation. However, the incomplete maintainer's author information and the new or inactive account raise some suspicion.

  • Incomplete maintainer's author information.
  • New or inactive maintainer account.
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external services.
  • Shell: No shell execution patterns detected, indicating no immediate risk from command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer's author information is incomplete and the account seems new or inactive, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Medium (6.2/10)

✦ High Test Suite 9.0

Test suite present — 2 test file(s) found

  • Test runner config found: pyproject.toml
  • 2 test file(s) detected (e.g. test_callback.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/aporthq/aport-agent-guardrails#readme
  • Detailed PyPI description (1655 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

  • 4 type-annotated function signatures (partial)
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 100 commits in aporthq/aport-agent-guardrails
  • Two distinct contributors found

🔬 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: aport.io>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository aporthq/aport-agent-guardrails 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 aport-agent-guardrails-langchain 
Create a mini-application called 'GuardedLangAgent' that serves as a communication layer between users and an AI agent, ensuring safe and controlled interactions through the use of guardrails and callbacks. This application will leverage the Python package 'aport-agent-guardrails-langchain' to manage asynchronous callbacks for AI tool calls, thereby enhancing security and user experience. Here’s a step-by-step guide on how to build it:

1. **Setup**: Begin by setting up your Python environment and installing necessary packages including 'aport-agent-guardrails-langchain', 'langchain', and any other dependencies required for handling asynchronous operations.
2. **Define User Interface**: Design a simple text-based UI where users can input commands or queries intended for the AI agent. This UI should also display responses from the AI agent.
3. **AI Agent Integration**: Integrate an existing AI agent (e.g., a chatbot or question-answering system) into your application. Ensure that the AI agent supports asynchronous processing and can accept callbacks.
4. **Implement Guardrails**: Use 'aport-agent-guardrails-langchain' to define guardrails around the AI agent’s capabilities. These guardrails should restrict the AI agent from performing certain actions or accessing sensitive information.
5. **Callback Handling**: Utilize the AsyncCallbackHandler provided by 'aport-agent-guardrails-langchain' to manage asynchronous callbacks. This handler will ensure that all tool calls made by the AI agent are monitored and controlled according to the defined guardrails.
6. **Security Measures**: Implement additional security measures such as input validation, error handling, and logging to further secure the interaction between the user and the AI agent.
7. **Testing and Deployment**: Thoroughly test the application to ensure that it functions as expected and that the guardrails effectively control the AI agent’s behavior. Once tested, deploy the application in a suitable environment for public or internal use.

Suggested Features:
- Dynamic guardrail configuration allowing users/admins to adjust security settings based on context.
- Detailed logging of all interactions for audit purposes.
- Support for multiple AI agents or tools within a single application instance.
- User authentication and role-based access control to limit who can interact with the AI agent.
- Customizable UI themes and layouts to enhance user experience.

💬 Discussion Feed

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