🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows no immediate signs of malicious intent in terms of network, shell, or obfuscation risks. However, the metadata risk score due to suspicious activity around the git repository and maintainer history raises concerns about potential supply-chain compromise.

Suspicious activity in git repository
Potential issues with maintainer history

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 signs of malicious activity.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: Suspicious activity around the git repository and maintainer history suggests potential risk.

🔬 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 5.0

Git history flags: Repository has zero stars and zero forks

Repository has zero stars and zero forks
All 8 commits happened within 24 hours

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Saikrishna" 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 agent-convo

Develop a fully-functional mini-app named 'ConvoSync' using the Python package 'agent-convo'. ConvoSync is designed to facilitate real-time, durable, and parallel conversations between multiple users through LangChain agents. This app will allow users to create conversation threads, join ongoing discussions, and ensure that their messages are not lost even if the server goes down temporarily.

Steps to Build ConvoSync:
1. Set up a Flask backend to handle user requests and manage session states.
2. Integrate 'agent-convo' to manage parallel conversations and ensure message durability.
3. Implement a WebSocket connection for real-time communication between clients and the server.
4. Create a simple React frontend that allows users to log in, create new threads, and join existing ones.
5. Ensure that each conversation thread is managed by a dedicated LangChain agent using 'agent-convo', which handles incoming messages and maintains the state of the conversation.
6. Implement a feature that allows users to view the history of a conversation, ensuring that all messages are stored and retrievable.
7. Add error handling to gracefully manage network issues and ensure messages are not lost.
8. Test the application thoroughly to ensure it works as expected under various conditions.

Suggested Features:
- User authentication to manage access to conversation threads.
- Real-time notifications when new messages are added to a thread.
- Ability to search through the conversation history.
- Support for multimedia messages such as images and videos.
- A mobile-responsive design for seamless use on different devices.

How 'agent-convo' is Utilized:
- Each conversation thread will be represented by a unique LangChain agent instance managed by 'agent-convo'.
- These agents will handle incoming messages from users, store them durably, and respond to queries about the conversation history.
- 'agent-convo' will ensure that conversations remain active even if the server experiences temporary downtime, maintaining the integrity of the chat sessions.