🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows moderate suspicion due to its low metadata quality and potential need for shell execution, though no concrete evidence of malicious intent has been found.

Metadata risk indicates low effort and potential lack of transparency.
Shell risk suggests potential for system-level actions.

Per-check LLM notes

Network: No network calls detected, which is normal.
Shell: Detection of shell execution patterns may indicate the package performs actions that require system-level permissions, but further investigation is needed to determine if these actions are legitimate or malicious.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets and credentials.
Metadata: The package shows signs of low effort and potential lack of transparency, raising some suspicion but not conclusive evidence of malice.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 5 shell execution pattern(s)

s try: result = subprocess.run(command, shell=True, check=True, stdout=subprocess.PIPE, std
s try: result = subprocess.run(['python', '-c', code], check=True, stdout=subprocess.PIPE,
s try: result = subprocess.run(['python', file], check=True, stdout=subprocess.PIPE, stderr
rt subprocess result = subprocess.run( ['findstr', pattern, file], stdout=subpro
ult = subprocess.run(command, shell=True, check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE

✓ 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

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 8.0

4 maintainer concern(s) found

Only one version has ever been released — brand new package
Author name is missing or very short
Author "" appears to have only 1 package on PyPI (new or inactive account)
Package has no PyPI classifiers (low effort / metadata quality)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with agentic_terminal

Create a command-line interface (CLI) utility called 'AgentShell' that leverages the 'agentic_terminal' package to provide advanced terminal capabilities to an AI agent. This utility will enable users to interact with an AI assistant through a terminal interface, allowing them to execute commands, run scripts, and manage tasks efficiently.

### Project Overview:
- **Name**: AgentShell
- **Description**: A CLI utility that integrates with an AI agent to perform various terminal operations such as executing shell commands, running Python scripts, and managing files.
- **Key Features**:
  - Interactive Shell: Users can type commands into the terminal and receive immediate responses from the AI agent.
  - Script Execution: Users can upload Python scripts to be executed within the terminal session.
  - File Management: Ability to create, read, update, and delete files directly from the terminal.
  - Task Scheduling: Schedule tasks to run at specific times using cron-like functionality.
  - Error Handling: Graceful error handling for both user input errors and execution errors.

### Utilizing 'agentic_terminal':
- **Initialization**: Start by initializing the 'agentic_terminal' package to set up the terminal environment for the AI agent.
- **Command Execution**: Use the package's capabilities to parse and execute user commands safely and efficiently.
- **Script Integration**: Integrate Python script execution by leveraging the package's support for running code snippets.
- **File Operations**: Implement file management features by utilizing the package's file handling utilities.
- **Task Scheduling**: Extend the package's functionality to include task scheduling for recurring tasks.
- **User Interface**: Design a clean and intuitive terminal interface for user interaction.

### Development Steps:
1. Set up the development environment with Python and install the necessary packages including 'agentic_terminal'.
2. Initialize the 'agentic_terminal' package and configure it for use in your project.
3. Develop the interactive shell feature allowing users to enter commands and receive responses.
4. Implement script execution functionality allowing users to upload and run Python scripts.
5. Add file management capabilities to create, read, update, and delete files.
6. Incorporate task scheduling to allow users to schedule tasks for later execution.
7. Ensure robust error handling is in place to handle any issues gracefully.
8. Test the application thoroughly to ensure all features work as expected.
9. Document the application and its usage clearly.
10. Deploy the application for users to start interacting with the AI agent through the terminal.