🤖 AI Analysis

Final verdict: SAFE

The package appears to be legitimate with no signs of obfuscation or credential harvesting. While the metadata suggests a potentially newer or less active maintainer, there are no other red flags.

Low obfuscation risk
Low credential risk
Single package from maintainer

Per-check LLM notes

Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
Credentials: No credential harvesting patterns detected, indicating low risk of malicious credential theft.
Metadata: The maintainer has only one package, which could indicate a new or less active account, but no other red flags are present.

🔬 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)

+ display_cmd) return subprocess.run( # noqa: S603 list(args), cwd=str(c

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Emmanuel Leblond" 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-as-unix-user

Create a mini-application named 'AgentShell' that leverages the 'agent-as-unix-user' Python package to simulate a secure and isolated environment for running user-defined scripts or commands. This application will act as a bridge between a user interface and the underlying system, ensuring that any actions taken within the sandboxed environment do not affect the broader system stability.

### Core Functionality:
1. **User Authentication:** Implement a simple authentication mechanism to verify users before they can run their scripts or commands. Users must log in with a username and password.
2. **Script Execution:** Allow authenticated users to upload and execute Python scripts or shell commands within a sandboxed environment. The sandboxing should be handled by the 'agent-as-unix-user' package, which will create a new UNIX user for each session, isolating it from the main system.
3. **Output Logging:** Capture and store all outputs (stdout and stderr) of the executed scripts or commands. These logs should be accessible to the user for debugging purposes.
4. **Resource Limitation:** Optionally, allow setting limits on CPU usage, memory, and execution time for each script/command run within the sandbox.
5. **Security Checks:** Before executing any script or command, perform basic security checks to prevent malicious code from being executed.

### Additional Features (Optional):
- **History Management:** Keep a history of previously executed scripts/commands and their outputs.
- **User Interface:** Develop a simple CLI or web-based UI for interacting with 'AgentShell'.
- **Customizable Sandbox Settings:** Provide options for users to customize their sandbox environment, such as installing specific packages or setting environment variables.

### Utilizing 'agent-as-unix-user':
- Use the package to dynamically create a new UNIX user for each user session, ensuring that any actions taken within the sandbox do not impact the main system.
- Leverage the package's capabilities to manage resource allocation and enforce isolation between different user sessions.
- Employ the package's mechanisms to securely handle file permissions and access control within the sandboxed environment.

Your task is to design and implement 'AgentShell', focusing on providing a secure, isolated environment for users to experiment with their code without risking the stability of the host system.