AI Analysis
Final verdict: SAFE
The package shows low network risk and shell risk that does not indicate malicious intent based on current information. The metadata suggests a possibly new developer but without additional red flags.
- No network calls detected.
- Potential shell execution capability but no specific commands identified.
Per-check LLM notes
- Network: No network calls detected, which is normal and expected.
- Shell: Shell execution capability is present but without specific commands, it's hard to assess intent; further review of the package's source code is recommended.
- Metadata: The author has only one package on PyPI, which may indicate a new or less active account, but there are no other suspicious flags.
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
Code Obfuscation
No obfuscation patterns detected
Shell / Subprocess Execution
score 2.0
Found 1 shell execution pattern(s)
) return 0 return subprocess.call(cmd) if __name__ == "__main__": sys.exit(main()) """T
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
Repository IndikaMaligaspe/agentforge appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "AgentForge contributors" 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 agentforge-runtime
Create a conversational AI assistant named 'ConvoBot' using the Python package 'agentforge-runtime'. ConvoBot should be capable of understanding natural language inputs, providing relevant responses, and performing specific tasks based on user commands. Here’s a detailed plan for building this mini-application: 1. **Setup Environment**: Ensure you have Python installed along with 'agentforge-runtime'. If not, install it via pip. 2. **Project Structure**: Define a clear directory structure for your project. Include folders for configuration files, data storage, logs, and source code. 3. **Initialization**: Use 'agentforge-runtime' to set up the initial framework of your project. This includes importing necessary modules and initializing any required services. 4. **User Interface**: Design a simple command-line interface (CLI) where users can interact with ConvoBot. Consider adding features like history logging, help documentation, and error handling. 5. **Natural Language Processing (NLP)**: Implement NLP capabilities using 'agentforge-runtime' functionalities. Train your model to understand different types of questions and commands from users. 6. **Task Execution**: Enable ConvoBot to perform tasks such as setting reminders, searching the web, or even controlling smart home devices based on user instructions. 7. **Integration with External Services**: Utilize 'agentforge-runtime' to integrate ConvoBot with external APIs for enhanced functionality. For example, integrating with weather APIs to provide current weather updates. 8. **Testing & Debugging**: Thoroughly test all functionalities to ensure reliability and accuracy. Use debugging tools provided by 'agentforge-runtime' to resolve any issues. 9. **Deployment**: Prepare ConvoBot for deployment. This might include packaging your application, setting up a server environment, and ensuring secure access. 10. **Documentation**: Provide comprehensive documentation detailing setup instructions, usage examples, and API references. By following these steps and leveraging the core features of 'agentforge-runtime', you will create a robust, user-friendly conversational AI assistant that can significantly enhance productivity and convenience.
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