🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits low risks in terms of network calls, shell execution, obfuscation, and credential handling. However, the metadata risk suggests potential issues with transparency and legitimacy.

Low metadata quality indicating potential lack of transparency.
No immediate malicious activities detected but overall package seems underdeveloped.

Per-check LLM notes

Network: The observed network call patterns indicate the package likely communicates with an external service, which is common for SDKs but should be verified against official documentation.
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 package shows signs of low effort and potential lack of transparency, raising concerns about its legitimacy.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

ut.""" self._client = httpx.Client( base_url=base_url.rstrip("/"), head
ut.""" self._client = httpx.AsyncClient( base_url=base_url.rstrip("/"), head

✓ 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 8.0

4 maintainer concern(s) found

Only one version has ever been released — brand new package
Author name is missing or very short
Author "" appears to have only 1 package on PyPI (new or inactive account)
Package has no PyPI classifiers (low effort / metadata quality)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with aethoncredit-sdk

Create a fully-functional mini-application called 'CreditScoreAnalyzer' using the 'aethoncredit-sdk' Python package. This application will allow users to input various personal financial information to receive a credit score analysis based on Aethon Credit Intelligence (ACI). Here are the steps and features your application should include:

1. **User Interface**: Develop a simple yet intuitive command-line interface (CLI) where users can input their financial details such as income, employment status, debt, and payment history.
2. **Data Validation**: Implement data validation checks to ensure the user inputs valid and realistic financial data.
3. **API Integration**: Utilize the 'aethoncredit-sdk' package to integrate with the ACI API. Use the SDK to send the validated financial data to the ACI API and retrieve the credit score analysis.
4. **Credit Score Analysis**: Display the credit score provided by ACI along with a brief analysis of the factors influencing the score.
5. **Recommendations**: Based on the credit score, provide personalized recommendations to improve the user's credit health. Suggestions could include tips on managing debt, paying bills on time, and increasing income.
6. **Logging and Error Handling**: Ensure the application logs all transactions and provides meaningful error messages if any issues arise during the process.
7. **Security Measures**: Implement basic security measures to protect user data, such as encrypting sensitive information before sending it to the ACI API.
8. **Documentation**: Write clear documentation explaining how to install the application, use the CLI, and interpret the results.

The 'aethoncredit-sdk' package is essential for this project as it provides the necessary functions to interact with the ACI API, making it easy to fetch credit score analyses based on the user's financial data. Your task is to create a useful tool that empowers individuals to understand their credit standing and take proactive steps towards improving it.