🤖 AI Analysis

Final verdict: SAFE

The package exhibits low risks across multiple dimensions including network, shell, and obfuscation. The metadata risk is slightly elevated due to the maintainer's single package, but this alone does not indicate malicious activity.

Low risk scores across all assessed categories.
Elevated metadata risk due to a single package from the maintainer.

Per-check LLM notes

Network: No network calls detected, which is normal if the package does not require external communications.
Shell: No shell execution detected, indicating the package does not perform system-level commands.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
Credentials: No credential harvesting patterns detected, indicating low risk of unauthorized data collection.
Metadata: The maintainer has only one package, indicating a new or less active account, which could be suspicious but not necessarily malicious.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 6 test file(s) found

6 test file(s) detected (e.g. test_core.py)

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (829 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

91 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

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

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-service

Develop a Python-based utility named 'CloudDataUploader' that leverages the 'aind-data-transfer-service' package to streamline the process of uploading files to cloud storage services like AWS S3 or Google Cloud Storage. This utility should be designed to cater to users who frequently need to transfer large datasets to the cloud for backup, sharing, or processing purposes.

The utility should include the following core functionalities:
1. User Authentication: Allow users to authenticate securely using OAuth2.0 protocol for cloud service providers like AWS and GCP.
2. File Selection Interface: Provide a simple GUI (Graphical User Interface) or command-line interface (CLI) where users can select multiple files or directories to upload.
3. Progress Tracking: Display real-time progress of file uploads with estimated time remaining.
4. Error Handling: Implement robust error handling mechanisms to manage issues such as network failures or quota limits.
5. Logging: Maintain logs of all upload activities including start time, end time, status (success/failure), and any errors encountered.
6. Configuration Management: Users should be able to configure their preferred cloud provider, bucket name, and other settings through a configuration file or environment variables.

To utilize the 'aind-data-transfer-service' package effectively, you will need to:
- Install the package via pip or directly from source code if it's not available on PyPI.
- Use its API to initiate the data transfer process, handling authentication tokens, upload requests, and response parsing.
- Customize the package's functionality to fit the specific needs of your utility, such as integrating with different cloud providers or enhancing security measures.

This project aims to provide a user-friendly yet powerful tool for managing cloud data transfers, making it easier for individuals and teams to efficiently store and access their data in the cloud.