actuarial-model-framework

v0.0.1 suspicious
4.0
Medium Risk

Actuarial Model Framework is a structured approach to building and managing actuarial models.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has a high metadata risk due to its recent creation, minimal activity, and single contributor. However, it shows no signs of malicious activity in terms of network calls, shell execution, or obfuscation.

  • High metadata risk
  • No detected malicious activities
Per-check LLM notes
  • Network: No network calls suggest the package is not attempting to communicate externally without reason.
  • Shell: No shell executions indicate the package does not run external commands that could pose a risk.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: High risk due to recent repository creation, minimal activity, single contributor, and sparse maintainer history.

🔬 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: proton.me>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 10.0

Git history flags: Repository created very recently: 5 day(s) ago (2026-05-31T15:20:35Z)

  • Repository created very recently: 5 day(s) ago (2026-05-31T15:20:35Z)
  • Repository has zero stars and zero forks
  • Very few commits: 2 total
  • Single contributor with only 2 commit(s) — possibly throwaway account
⚠ Maintainer History score 6.0

3 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)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with actuarial-model-framework 
Create a fully-functional mini-application that utilizes the 'actuarial-model-framework' package to manage and analyze insurance risk portfolios. Your application should allow users to input various types of insurance policies and their associated risk factors. It should then use the framework to model potential outcomes based on these inputs. Here’s a detailed breakdown of the steps and features your application should include:

1. **User Interface**: Develop a simple yet intuitive UI where users can input policy details such as type of insurance, premium amount, coverage limits, deductibles, and other relevant risk factors.
2. **Data Input Handling**: Implement a backend system that validates user inputs and stores them in a structured format suitable for processing by the 'actuarial-model-framework'.
3. **Model Building**: Utilize the 'actuarial-model-framework' package to build actuarial models based on the input data. This involves defining different scenarios and assumptions for risk analysis.
4. **Risk Analysis**: Use the framework to run simulations and generate reports that show the potential financial impact of various risks on the insurance portfolio. Include visualizations like graphs and charts to make the data more accessible.
5. **Scenario Testing**: Allow users to test different scenarios by adjusting parameters such as economic conditions, mortality rates, etc., and observe how these changes affect the risk profile of the portfolio.
6. **Reporting**: Provide a feature that generates comprehensive reports summarizing the risk assessment, including key metrics and recommendations based on the analysis.
7. **Documentation and Support**: Ensure all code is well-documented, and include a brief guide explaining how to use the application and interpret its results.

By following these steps and incorporating these features, you will create a valuable tool for anyone involved in managing insurance risk portfolios.