🤖 AI Analysis

Final verdict: SAFE

The package appears to be legitimate with low risks across multiple categories. The only minor concern is the metadata risk due to the maintainer's details being incomplete.

Low network, shell, obfuscation, and credential risks.
Minor metadata risk due to incomplete maintainer details.

Per-check LLM notes

Network: The use of network calls with session management and JSON content type is common for API interactions, indicating legitimate data exchange rather than malicious activity.
Shell: No shell execution patterns were detected.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The maintainer's author name is missing and they appear to be inactive or new, raising some suspicion but not conclusive evidence of malice.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

quests.Session: session = requests.Session() headers = { "Content-Type": "application/json"
else: response = requests.get(url, stream=True, timeout=120) response.raise_for_st
else: response = requests.get(pack.url, timeout=30) response.raise_for_status(

✓ 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

Repository datahub-project/datahub appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author name is missing or very short
Author "" 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 acryl-datahub

Create a mini-application named 'DataHubExplorer' that leverages the 'acryl-datahub' package to interact with the DataHub metadata store. This application will serve as a user-friendly interface for managing and exploring metadata within a DataHub instance. Here are the key functionalities your app should have:

1. **User Authentication**: Implement a login feature where users can authenticate themselves using their DataHub credentials.
2. **Metadata Browsing**: Allow users to browse through different types of metadata (e.g., datasets, tables, metrics) available in the DataHub instance.
3. **Search Functionality**: Enable users to search for specific metadata items based on various criteria such as name, description, tags, etc.
4. **Metadata Details View**: When a user selects a specific metadata item, display detailed information about it, including its properties, lineage, and associated metrics.
5. **Metadata Management**: Provide basic CRUD (Create, Read, Update, Delete) operations for metadata items. Users should be able to create new entries, update existing ones, and delete unnecessary data.
6. **Lineage Visualization**: Integrate a feature that visualizes the lineage of selected metadata items, showing how they relate to other datasets or tables.
7. **Notifications**: Set up a system where users receive notifications about changes or updates to specific metadata items they are interested in.

To achieve these functionalities, utilize the 'acryl-datahub' package to connect to the DataHub instance, fetch metadata, and perform necessary operations. Your application should also handle errors gracefully and provide informative feedback to the user at each step.