AI Analysis
Final verdict: SAFE
The package is considered safe based on the low risk scores for obfuscation and credential handling. However, the metadata suggests the maintainer may be new or less active.
- Low obfuscation risk
- No credential harvesting detected
- Single package from maintainer with no GitHub repo
Per-check LLM notes
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
- Credentials: No credential harvesting patterns detected, suggesting the package does not engage in suspicious activity concerning secret or credential handling.
- Metadata: The maintainer has only one package and lacks a GitHub repository, which may indicate a new or less active account.
Package Quality Overall: Low (4.4/10)
✦ High
Test Suite
9.0
Test suite present — 3 test file(s) found
3 test file(s) detected (e.g. __init__.py)
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (9109 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
15 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
No suspicious network call patterns found
Code Obfuscation
No obfuscation patterns detected
Shell / Subprocess Execution
score 6.0
Found 3 shell execution pattern(s)
nd.append("--dryrun") subprocess.run(command, check=True, shell=shell) def _upload_directorym() == "Windows": shell = True else: shell = False command = [check=True, shell=True, ) @patch( "aind_data_transfer_lite.up
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 2.0
1 maintainer concern(s) found
Author "Allen Institute for Neural Dynamics" 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 aind-data-transfer-lite
Create a mini-application called 'DataMover' using Python that facilitates efficient data transfer between different storage systems such as local filesystems, cloud storages like AWS S3, Google Cloud Storage, and Azure Blob Storage. This application should leverage the 'aind-data-transfer-lite' package to handle the data transfer processes seamlessly. Here’s a detailed breakdown of what your application should achieve: 1. **User Interface**: Design a simple and intuitive command-line interface (CLI) where users can specify the source and destination of their data transfer operations. 2. **Configuration Management**: Implement configuration files or environment variables to store credentials and settings required for connecting to various storage systems. 3. **Data Transfer Operations**: Utilize 'aind-data-transfer-lite' to perform basic data transfer operations including upload, download, copy, move, and delete. Ensure these operations are robust and can handle large datasets efficiently. 4. **Error Handling**: Incorporate comprehensive error handling mechanisms to manage exceptions gracefully during data transfers, providing meaningful feedback to the user. 5. **Logging and Reporting**: Integrate logging capabilities to record all actions performed by the application and generate reports summarizing successful and failed operations. 6. **Security Features**: Implement security measures to protect sensitive information such as access keys and ensure data integrity during transfers. 7. **Testing and Documentation**: Develop thorough unit tests to validate the functionality of your application and write clear documentation explaining how to install, configure, and use DataMover. The 'aind-data-transfer-lite' package will primarily be used for executing the actual data transfer tasks. It abstracts away the complexities involved in interfacing with different storage systems, allowing you to focus on building a user-friendly and feature-rich application. Your goal is to create a versatile tool that simplifies the process of moving data across diverse environments, making it accessible to users with varying levels of technical expertise.
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