🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits several indicators that suggest potential security concerns, particularly around shell execution and credential handling, which could pose significant risks if misused.

Shell execution for commands like 'pip list' and 'ssh'
Accessing identity files like ~/.ssh/id_rsa

Per-check LLM notes

Network: The network call pattern is likely used for fetching configuration or updating from a remote source, which is not inherently suspicious but should be reviewed for the destination URL.
Shell: Shell execution is used to run commands like 'pip list' and 'ssh', which might be part of package functionality but could indicate potential risk if not properly controlled or documented.
Obfuscation: The use of base64 and zlib for data compression/encoding is common but could be used to hide malicious content.
Credentials: Accessing identity files like ~/.ssh/id_rsa without proper context suggests potential unauthorized access risks.
Metadata: The presence of a non-HTTPS link and a single package from the maintainer suggest potential lack of maintenance or oversight.

📦 Package Quality Overall: Medium (6.6/10)

✦ High Test Suite 9.0

Test suite present — 11 test file(s) found

Test runner config found: pyproject.toml
11 test file(s) detected (e.g. test_bug_report.py)

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (2254 chars)

○ Low Contributing Guide 4.0

No contributing guide or governance files found

Development Status classifier >= Beta

◈ Medium Type Annotations 5.0

Partial type annotation coverage

18 type-annotated function signatures detected in source

✦ High Multiple Contributors 10.0

Active multi-contributor project

9 unique contributor(s) across 100 commits in aiidalab/aiidalab-widgets-base
Active community — 5 or more distinct contributors

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

try: database = requests.get(database_source).json() except Exception:

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

data = json.loads( zlib.decompress(base64.urlsafe_b64decode(fingerprint)).decode(encoding)

⚠ Shell / Subprocess Execution score 10.0

Found 5 shell execution pattern(s)

= sys.executable output = subprocess.run( [python_bin, "-m", "pip", "list", "--format=json"],
t fpath.exists(): subprocess.run(keygen_cmd, capture_output=True, check=True) def _can_l
word will fail. ret = subprocess.call( [ "ssh", self.h
/i>' process_result = subprocess.run( ["verdi", "computer", "test", "--print-tracebac
mp(), "export.aiida") subprocess.call( ["verdi", "archive", "create", fname, "-N", str

⚠ Credential Harvesting score 2.5

Found 1 credential access pattern(s)

(sshcfg.get("identityfile", ["~/.ssh/id_rsa"])[0]).expanduser() ), "timeout": 6

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: materialscloud.org

⚠ Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

Non-HTTPS external link: http://www.max-centre.eu/

✓ Git Repository History

Repository aiidalab/aiidalab-widgets-base appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "The AiiDAlab team" 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 aiidalab-widgets-base

Create a mini-application that leverages the 'aiidalab-widgets-base' Python package to facilitate user interaction with AiiDA workflows. This application will serve as a simplified interface for users who want to execute predefined computational materials science workflows without needing to understand the underlying complexity of AiiDA.

### Project Goals:
- Develop an intuitive GUI using JupyterLab or similar environment.
- Allow users to select from a list of predefined workflows (e.g., electronic structure calculations, molecular dynamics).
- Provide input parameters customization options for each workflow.
- Enable users to submit their selected workflow with custom parameters to a remote AiiDA instance.
- Display real-time progress and results of the submitted workflow through interactive widgets.

### Key Features:
1. **Workflow Selection**: Implement a dropdown menu to allow users to choose from various workflows supported by AiiDA.
2. **Parameter Customization**: Use widgets such as sliders, text inputs, checkboxes to enable users to modify default input parameters for the selected workflow.
3. **Submission Interface**: Create a submission button that triggers the execution of the chosen workflow with specified parameters on a remote AiiDA instance.
4. **Progress Monitoring**: Integrate widgets to monitor the progress of the running workflow, including status updates and estimated time remaining.
5. **Result Visualization**: Upon completion, display the output of the workflow using appropriate visualization tools, such as graphs or tables, based on the nature of the workflow.

### Utilizing 'aiidalab-widgets-base':
- Use the 'aiidalab_widgets_base' package to create the graphical components of your application, ensuring they are compatible with JupyterLab.
- Leverage the package's built-in widgets for parameter customization, workflow selection, and result visualization.
- Explore how these widgets can enhance user experience and make complex interactions more accessible.

### Development Steps:
1. **Setup Environment**: Ensure you have a working installation of Python, JupyterLab, and 'aiidalab-widgets-base'.
2. **Design Layout**: Sketch out the layout of your application, focusing on user-friendly design principles.
3. **Widget Integration**: Begin integrating widgets from 'aiidalab-widgets-base' into your application, starting with workflow selection and parameter customization.
4. **Backend Connection**: Develop the backend logic to connect with a remote AiiDA instance and handle workflow submissions.
5. **Testing & Refinement**: Test your application thoroughly, making adjustments based on feedback and usability testing.
6. **Documentation**: Write clear documentation explaining how to use your application and any dependencies required.