apokalypsis

v0.0.1 suspicious
4.0
Medium Risk

uv based llm tool

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has no detected malicious activities such as network calls or shell executions, but its metadata quality and maintainer activity are concerning. This could suggest potential supply-chain risks.

  • Low maintainer activity
  • Poor metadata quality
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package's functionality requires external communications.
  • Shell: No shell execution detected, indicating that the package does not appear to execute system commands without user interaction.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows signs of low maintainer activity and poor metadata quality, which may indicate potential risks.

📦 Package Quality Overall: Low (1.2/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
○ Low Documentation 1.0

No documentation detected

  • No documentation URL, doc files, or meaningful description found
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
○ 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

Email domain looks legitimate: aiornot.com>

✓ 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 apokalypsis 
Create a mini-application called 'ApocalypseAnalyzer' using the Python package 'apokalypsis'. This application will serve as a tool for users to analyze potential apocalyptic scenarios based on user input. The app will take in data such as population density, resource availability, and environmental factors, and then use 'apokalypsis' to simulate the impact of various hypothetical disasters or events. Here are the steps and features for your application:

1. **User Interface**: Design a simple yet intuitive command-line interface where users can input scenario parameters.
2. **Data Input**: Allow users to specify parameters such as population density, resource distribution, and environmental conditions.
3. **Scenario Selection**: Provide a selection of predefined disaster scenarios like pandemics, natural disasters, or economic collapse.
4. **Simulation Execution**: Use 'apokalypsis' to run simulations based on the user inputs and selected scenario. The package's UV-based LLM capabilities will help in predicting outcomes and impacts.
5. **Results Presentation**: Display the results of the simulation in an easy-to-understand format, showing survival rates, affected regions, and recovery timelines.
6. **Additional Features**:
   - Historical Data Analysis: Allow users to load historical data to compare past events with simulated scenarios.
   - Custom Scenario Creation: Enable advanced users to create their own scenarios.
   - Visualization Tools: Integrate basic visualization tools to graphically represent the simulation outcomes.
7. **Documentation**: Write comprehensive documentation detailing how to install the application, input data, and interpret the results.

Utilize 'apokalypsis' throughout the development process to enhance the predictive accuracy and depth of analysis provided by your ApocalypseAnalyzer.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!