AI Analysis
Final verdict: SAFE
The package appears safe with no network or shell risks. However, the low community engagement and inactive maintainer status slightly increase the metadata risk.
- No network or shell risks detected.
- Low community engagement and inactive maintainer.
Per-check LLM notes
- Network: No network calls detected, which is typical unless the package requires internet access for its functionality.
- Shell: No shell execution detected, indicating the package does not attempt to execute system commands.
- Metadata: The repository's lack of community engagement and the maintainer's new/inactive status raise some concerns.
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: example.com>
Suspicious Page Links
All external links appear legitimate
Git Repository History
score 2.5
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
Maintainer History
score 4.0
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" 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 AntFlow
Create a mini-application called 'AsyncFileProcessor' using the Python package 'AntFlow'. This application will serve as a powerful tool for processing large files asynchronously, making use of the package's concurrent futures-style API and advanced pipeline capabilities. Here are the steps and features you need to implement: 1. **Project Setup**: Initialize a new Python virtual environment and install the necessary packages including AntFlow. 2. **Basic Functionality**: Implement a function to read a file line by line asynchronously. Use AntFlow's `submit` method to schedule tasks for each line of the file. 3. **Processing Pipeline**: Design a processing pipeline where each line of the file is processed through multiple stages such as cleaning, transformation, and validation. Utilize AntFlow's pipeline feature to chain these operations together efficiently. 4. **Concurrency Control**: Allow users to specify the maximum number of concurrent tasks that can run at once. AntFlow's concurrency management features should be leveraged here. 5. **Error Handling**: Implement robust error handling mechanisms. If any stage of the pipeline fails, the application should log the error and continue processing other lines. 6. **Output Generation**: After all lines have been processed, generate a report summarizing the number of lines processed, the time taken, and any errors encountered during processing. 7. **User Interface**: Develop a simple command-line interface (CLI) where users can input the path to the file they wish to process and configure parameters like the number of concurrent tasks. 8. **Testing**: Write unit tests to ensure each component of your application works as expected under various conditions. 9. **Documentation**: Provide comprehensive documentation on how to install and use the AsyncFileProcessor, including examples of typical usage scenarios. By completing this project, you'll gain hands-on experience with asynchronous programming and advanced task management using the AntFlow library.