AI Analysis
Final verdict: SAFE
The package ajlab v0.1.8 poses minimal risk based on the provided analysis notes. It does not engage in network calls, shell execution, or obfuscation, and there are no signs of credential harvesting.
- No network calls
- No shell execution
- No obfuscation patterns
- No credential harvesting patterns
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: The maintainer has only one package, which may indicate a new or less active account.
Package Quality Overall: Low (3.0/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (1847 chars)
○ 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
◈ Medium
Multiple Contributors
6.0
Limited contributor diversity
2 unique contributor(s) across 26 commits in jtpio/ajlabTwo distinct contributors found
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
No author email provided
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository jtpio/ajlab appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Jeremy Tuloup" 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 ajlab
Your task is to develop a versatile mini-app that leverages the 'ajlab' package to create an interactive, agent-based modeling environment within JupyterLab. This application will allow users to simulate various scenarios using agent-based models (ABMs), which are computational models used to simulate the actions and interactions of autonomous agents (such as individuals or organizations) to assess their effects on the system as a whole. Step 1: Setup the Environment - Install the 'ajlab' package along with other necessary libraries such as JupyterLab, NumPy, and Matplotlib. - Configure your JupyterLab environment to include custom extensions or themes if desired. Step 2: Define Core Features - Implement a user-friendly interface where users can input parameters for different types of agents and environments. - Enable users to visualize the simulation results in real-time through interactive plots and graphs. - Provide options for saving and loading simulation scenarios. Step 3: Utilize 'ajlab' - Use 'ajlab' to integrate your ABM framework into JupyterLab, ensuring seamless interaction between the model and the visualization tools. - Leverage 'ajlab' to manage the lifecycle of the simulations, including starting, stopping, and pausing them. Suggested Features: - Customizable agent behaviors based on user inputs. - Different environmental conditions that affect agent behavior. - Real-time feedback mechanisms for adjusting simulation parameters mid-run. - Detailed reports and analytics at the end of each simulation session. Your goal is to create a tool that not only demonstrates the power of agent-based modeling but also showcases the flexibility and interactivity provided by the 'ajlab' package within a JupyterLab setting.
💬 Discussion Feed
No discussion yet. Be the first to share your thoughts!
Report Abuse / Security Issue