arcline

v0.0.1.dev0 suspicious
4.0
Medium Risk

A Python Framework for Supply Chain Network Optimizer

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has low risks in terms of network calls, shell execution, obfuscation, and credential handling. However, the metadata risk score of 7 out of 10 raises suspicion due to the lack of detailed information from the author.

  • Metadata risk score of 7/10
  • Minimal information provided by the author
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires internet access for its functionality.
  • Shell: No shell execution detected, indicating the package does not execute external commands.
  • Obfuscation: No obfuscation patterns detected, suggesting low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, indicating safe handling of secrets and credentials.
  • Metadata: The package shows signs of being newly created with minimal information provided by the author, raising concerns about its legitimacy and purpose.

📦 Package Quality Overall: Low (2.0/10)

○ 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 (1375 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
○ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 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: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ 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 arcline 
Create a mini-application named 'SupplyChainOptimizer' using the 'arcline' Python package. This application will serve as a basic supply chain network optimizer, helping businesses visualize and optimize their supply chains. The app should allow users to input data about suppliers, warehouses, and retailers, including locations and capacities. It should then use 'arcline' to model and optimize the supply chain network based on cost minimization and service level objectives. Here are the steps and features to include:

1. **User Interface**: Develop a simple web-based UI using Flask or Django where users can input details of their supply chain nodes (suppliers, warehouses, retailers).
2. **Data Input**: Users should be able to enter node names, locations (latitude/longitude), capacities, and demand forecasts.
3. **Network Modeling**: Utilize 'arcline' to create a network model from the user-provided data. This involves defining arcs (connections between nodes) and associated costs.
4. **Optimization Engine**: Implement an optimization engine within 'arcline' to find the most cost-effective distribution plan while meeting all demands.
5. **Visualization**: Integrate a mapping library like Folium to visually represent the optimized supply chain network, highlighting key nodes and optimal paths.
6. **Report Generation**: Provide functionality to generate a report summarizing the optimized network, including total cost savings and performance metrics.
7. **Testing and Validation**: Include automated tests to validate the correctness of the optimization process and ensure the UI functions as expected.

This project aims to demonstrate how 'arcline' can be leveraged to solve real-world supply chain management challenges efficiently.

💬 Discussion Feed

Leave a comment

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