AI Analysis
Final verdict: SUSPICIOUS
The package shows no direct signs of malicious intent but the maintainer's limited activity and lack of a GitHub repository raise some concerns about its legitimacy.
- Maintainer has only one package
- No associated GitHub repository
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires network functionality.
- Shell: No shell execution patterns detected, indicating no immediate risk of unauthorized system command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
- Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
- Metadata: The maintainer has only one package and no associated GitHub repository, which may indicate a less experienced or potentially suspicious account.
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
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 2.0
1 maintainer concern(s) found
Author "arrayyy" 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 arrayyy
Create a fully-functional mini-application called 'GraphSolver' that leverages the 'arrayyy' package to solve common graph problems encountered in competitive programming. The application should allow users to input their own graph data (either as an adjacency matrix or list) and specify which algorithm they want to run on the graph. Here’s a detailed breakdown of the project requirements: 1. **User Interface**: Develop a simple command-line interface (CLI) where users can interactively input their graph data and choose from a list of available algorithms. 2. **Graph Representation**: Allow users to represent their graphs using either an adjacency matrix or an adjacency list. Ensure that the application validates the input data to ensure it forms a valid graph. 3. **Algorithm Selection**: Implement at least three different algorithms from the 'arrayyy' package, such as Dijkstra's shortest path algorithm, Depth-First Search (DFS), and Breadth-First Search (BFS). Each algorithm should output the results in a clear and understandable format. 4. **Result Display**: After running an algorithm, display the results clearly. For example, if running Dijkstra's algorithm, show the shortest path from a source node to all other nodes. 5. **Error Handling**: Incorporate robust error handling to manage invalid inputs and edge cases gracefully. 6. **Documentation**: Write comprehensive documentation explaining how to use the GraphSolver application, including examples of valid input formats and expected outputs. The 'arrayyy' package is utilized throughout the application to handle the underlying graph operations efficiently. By leveraging its tree and graph algorithms, you can focus more on the user interaction and result presentation rather than implementing low-level graph algorithms from scratch.
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