agentscope-runtime

v1.1.6.post2 suspicious
5.0
Medium Risk

A production-ready runtime framework for agent applications, providing secure sandboxed execution environments and scalable deployment solutions with multi-framework support.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows some signs of potential risk, particularly regarding network and metadata concerns, but lacks clear indicators of malicious intent.

  • network risk due to external URL calls
  • metadata risk due to suspicious lack of HTTPS links and missing author details
Per-check LLM notes
  • Network: Network calls to external URLs with JSON payloads could indicate legitimate API interactions, but further investigation is needed to ensure no unauthorized data transmission.
  • Shell: No shell execution patterns detected, which suggests low risk of direct system command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: Suspicious lack of HTTPS links and missing author details suggest potential risk.

📦 Package Quality Overall: Low (4.2/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (47675 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Type checker (mypy / pyright / pytype) referenced in project
  • 131 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

  • streaming response = requests.post( url, json=payload, head
  • response = requests.post( url, json=p
✓ 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 score 10.0

Found 6 suspicious link(s) on the package page

  • Non-HTTPS external link: http://webui.runtime.agentscope.io/
  • Non-HTTPS external link: http://www.apache.org/licenses/LICENSE-2.0
  • Non-HTTPS external link: http://www.bruceluo.net/
  • Non-HTTPS external link: http://ceshihao.github.io
  • Non-HTTPS external link: http://lokk.cn/about
  • Non-HTTPS external link: http://dorianzheng.github.io
✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • 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 agentscope-runtime 
Create a Python-based mini-application that acts as a secure, sandboxed environment for running user-uploaded Python scripts within a controlled and isolated space. This application will leverage the 'agentscope-runtime' package to ensure that these scripts are executed safely without posing security risks to the host system. The goal is to provide a simple yet powerful tool for developers to test their code snippets in a safe, isolated environment before deploying them in production settings.

### Application Requirements:
1. **User Interface**: Develop a basic command-line interface (CLI) where users can upload Python scripts (.py files).
2. **Execution Environment**: Use 'agentscope-runtime' to create a secure sandboxed environment for executing these scripts. Ensure that the environment restricts access to the file system, network, and other critical resources on the host machine.
3. **Resource Limits**: Implement functionality to set time and memory limits for script execution to prevent infinite loops or excessive resource consumption.
4. **Logging and Reporting**: Capture and display logs from script execution, including any errors or warnings, to help users debug their code.
5. **Framework Support**: Demonstrate multi-framework support by allowing users to specify the Python version or additional libraries required for their scripts.
6. **Security Features**: Highlight the security features provided by 'agentscope-runtime', such as secure isolation and monitoring of the execution environment.
7. **Deployment Options**: Explore how 'agentscope-runtime' supports scalable deployment options, even if this feature is not directly implemented in the CLI version of the app.

### Development Steps:
1. Set up your development environment with Python and install the 'agentscope-runtime' package.
2. Design the CLI interface using Python’s built-in modules or a third-party library like Click for better CLI experience.
3. Integrate 'agentscope-runtime' into your application to handle script execution securely.
4. Implement logging mechanisms to capture and report script execution details.
5. Test your application thoroughly with various Python scripts to ensure it meets all specified requirements.
6. Document your setup process, code structure, and usage instructions clearly.

By following these steps, you'll develop a useful and secure tool that leverages 'agentscope-runtime' to provide a safe environment for testing and experimenting with Python code snippets.