aisolate-client

v0.2.0 suspicious
6.0
Medium Risk

Client library for sandbox environments

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits signs of potential risk due to low maintainer activity and missing standard metadata, although there is no concrete evidence of malicious intent.

  • Low maintainer activity and missing standard metadata increase suspicion.
  • Incomplete license information raises concerns.
Per-check LLM notes
  • Metadata: The package shows low maintainer activity and lacks standard metadata, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 5 test file(s) found

  • Test runner config found: conftest.py
  • 5 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 5.0

Some documentation present

  • Brief PyPI description (313 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 5.0

Partial type annotation coverage

  • 67 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)

  • try: with socket.create_connection((host, port), timeout=0.2): return e
  • } self._session = httpx.AsyncClient( base_url=self.base_url, timeout=self._timeo
⚠ Code Obfuscation score 6.0

Found 3 obfuscation pattern(s)

  • final_answer = pickle.loads(base64.b64decode(error.error_value)) return CodeOutput(
  • try: return base64.b64decode(payload) except (ValueError, TypeError):
  • final_answer = pickle.loads(base64.b64decode(error.error_value)) return
⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • ["NO_COLOR"] = "1" proc = subprocess.Popen( cmd, stdout=subprocess.PIPE, stderr
✓ 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 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 aisolate-client 
Your task is to develop a mini-application that leverages the 'aisolate-client' Python package to create and manage sandboxed environments for testing software components. This application will allow developers to easily set up isolated testing environments, ensuring that tests run independently without affecting other parts of the system.

### Project Overview:
- **Name**: Sandbox Tester
- **Purpose**: To provide a user-friendly interface for setting up, managing, and tearing down sandbox environments using 'aisolate-client'.
- **Target Audience**: Developers who need to test their applications in isolated, controlled environments.

### Core Features:
1. **Environment Setup**:
   - Allow users to define the scope of the sandbox environment (e.g., specific directories or processes).
   - Automatically configure the sandbox based on user inputs.
2. **Resource Management**:
   - Monitor and control resource usage within the sandbox (e.g., CPU, memory, network).
3. **Test Execution**:
   - Integrate with popular testing frameworks (e.g., pytest, unittest) to run tests within the sandbox.
4. **Teardown**:
   - Safely shut down the sandbox environment after testing is complete.
5. **Logging & Reporting**:
   - Provide detailed logs of the sandbox setup and test execution.
   - Generate reports summarizing test results and resource usage.

### Utilization of 'aisolate-client':
- Use 'aisolate-client' to create sandbox environments where tests are executed. This ensures that each test runs in isolation, preventing interference from other tests or the host system.
- Leverage the package's capabilities to manage resources within the sandbox, ensuring that tests do not consume excessive resources.
- Implement features to monitor and log activities within the sandbox, providing transparency into how tests are running and what resources they are consuming.

### Additional Suggestions:
- Develop a command-line interface (CLI) for easy interaction with the application.
- Consider adding support for different types of environments (e.g., Docker containers, virtual machines) if 'aisolate-client' supports it.
- Include a feature to save and restore sandbox configurations for reproducibility.
- Explore integrating with continuous integration/continuous deployment (CI/CD) systems to automate the testing process.

### Expected Outcome:
By the end of this project, you should have a fully functional mini-application that simplifies the process of setting up, managing, and tearing down sandbox environments for software testing. This tool should significantly enhance the efficiency and reliability of your testing workflows.

💬 Discussion Feed

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