agenome

v0.1.1 suspicious
5.0
Medium Risk

Agent genome hub — sync AI agent identity, memory, and sessions across machines and frameworks

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has some unusual behaviors such as initiating a local Git repository, and lacks detailed maintainer information. These factors raise concerns but do not conclusively indicate malicious intent.

  • Unusual behavior of initiating a local Git repository
  • Sparse maintainer information
Per-check LLM notes
  • Network: No network calls detected, indicating low risk.
  • Shell: Git commands suggest the package is initializing a local Git repository, which is unusual and may indicate unexpected behavior or preparation for version control within the user's environment.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The repository is not found, and the maintainer information is sparse, indicating potential unreliability.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • git_dir.exists(): subprocess.run( ["git", "init", "-b", "main"],
  • out global config subprocess.run( ["git", "config", "user.name", "Agenome"],
  • ue, ) subprocess.run( ["git", "config", "user.email", "agenome@lo
  • t be missing) r = subprocess.run( ["git", "config", "user.name"],
  • dout.strip(): subprocess.run( ["git", "config", "user.name", "Agenome
  • ) subprocess.run( ["git", "config", "user.email", "agenom
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: users.noreply.github.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ 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 agenome 
Create a mini-application named 'AgentSync' using Python that leverages the 'agenome' package to synchronize AI agents across different machines and frameworks. This application should allow users to manage their AI agent's identity, memory, and session data seamlessly. Here are the steps and features to implement:

1. **Setup Environment**: Ensure you have Python installed on your machine. Install the 'agenome' package along with any other necessary dependencies.

2. **User Authentication**: Implement a simple user authentication system where users can sign up or log in. This will allow personalized data management for each user.

3. **AI Agent Management**: Users should be able to create, edit, delete, and view details of their AI agents. Each agent should have a unique identifier and can store information such as name, purpose, and framework.

4. **Data Synchronization**: Utilize the 'agenome' package to enable real-time synchronization of AI agent data (identity, memory, and sessions) across multiple devices or platforms. This feature ensures that users can access and manage their AI agents from anywhere.

5. **Memory Management**: Allow users to add, modify, and remove memories associated with their AI agents. Memories could include learned data, experiences, or notes that help shape the agent's behavior.

6. **Session Tracking**: Implement session tracking functionality where users can start, stop, and review past sessions of their AI agents. Sessions should capture interactions and learning outcomes to improve future performance.

7. **Cross-Platform Compatibility**: Ensure that 'AgentSync' works seamlessly across various operating systems and cloud environments, leveraging the 'agenome' package's capabilities to handle cross-platform data synchronization efficiently.

8. **Security Measures**: Incorporate basic security measures such as encryption for stored data and secure communication channels when transferring data between devices.

9. **User Interface**: Develop a user-friendly interface for managing AI agents. This could be a command-line interface (CLI) or a graphical user interface (GUI), depending on the target audience and complexity.

By following these steps and implementing these features, 'AgentSync' will provide a robust solution for managing and synchronizing AI agents across different machines and frameworks, making it easier for developers and enthusiasts to work with AI agents without worrying about data consistency.