🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has low risks for common attack vectors like network calls, shell execution, and credential harvesting. However, the presence of suspicious non-HTTPS links and the lack of maintainer history elevate the risk to a suspicious level.

Suspicious non-HTTPS links
Lack of maintainer history

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: No shell execution patterns detected, indicating no immediate risk of command execution.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: Suspicious non-HTTPS links and lack of maintainer history suggest potential risk, but no clear evidence of typosquatting or malicious intent.

🔬 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

Email domain looks legitimate: iqvia.com>

⚠ Suspicious Page Links score 4.0

Found 2 suspicious link(s) on the package page

Non-HTTPS external link: http://rwes-gitlab01.internal.imsglobal.com/python-microservice-clients/e360-ana
Non-HTTPS external link: http://rwes-gitlab01.internal.imsglobal.com/python-microservice-clients/e360-ana

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ 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 adt-clients

Create a data analysis tool using the 'adt-clients' Python package which connects to the E360 Analytic Dataset Tools platform. Your task is to develop a command-line interface (CLI) application that allows users to interact with datasets hosted on the E360 platform. This tool should enable users to perform basic CRUD operations (Create, Read, Update, Delete) on datasets, as well as execute predefined analytical queries and visualize the results.

Steps to follow:
1. Install the 'adt-clients' package using pip.
2. Set up the CLI application using Python's argparse module for command handling.
3. Implement authentication mechanisms to securely connect to the E360 platform.
4. Develop functions to handle dataset creation, retrieval, updating, and deletion.
5. Integrate functionality to run pre-defined analytical queries against the datasets.
6. Use matplotlib or seaborn for visualizing the query results.
7. Add error handling and logging for better user experience and debugging.
8. Document your code thoroughly, including examples of how to use each feature.
9. Test your application with sample datasets provided by the E360 platform.

Suggested Features:
- Support for multiple authentication methods (API keys, OAuth tokens).
- Ability to schedule regular updates or checks for datasets.
- Exporting query results to CSV or Excel formats.
- Interactive mode for exploratory data analysis sessions.
- Integration with Jupyter notebooks for extended analysis capabilities.