AI Analysis
The package has a moderate risk score due to metadata concerns, but no direct evidence of malicious activities like network calls or shell executions was found.
- Metadata risk with non-secure external links, missing repository, and potential fake maintainer.
- Low risk for network calls, shell execution, obfuscation, and credential harvesting.
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require external communications.
- Shell: No shell execution patterns detected, indicating the package likely does not execute system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows several red flags including a non-secure external link, an absent repository, and a potentially fake maintainer.
Package Quality Overall: Low (2.0/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Detailed PyPI description (1894 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
No type annotations detected
No type annotations, py.typed marker, or stub files detected
Could not retrieve contributor data from GitHub
GitHub API error: 404
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
No author email provided
Found 1 suspicious link(s) on the package page
Non-HTTPS external link: http://127.0.0.1:7890
Repository not found (deleted or private)
Repository not found (deleted or private)
3 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a mini web automation tool using Python and the 'autoscript-hub-sdk' package. This tool will allow users to automate repetitive tasks on websites, such as filling out forms or scraping data, with minimal effort. The application should be designed to be user-friendly, allowing both novice and experienced users to create and run their own scripts easily. Step 1: Setup the Environment - Install Python and necessary packages including 'autoscript-hub-sdk'. - Set up a virtual environment for your project. Step 2: Define Core Functionality - Use 'autoscript-hub-sdk' to automatically configure the browser settings, proxy settings, and output directories needed for running scripts. - Implement a simple script editor within the tool where users can write their automation scripts. - Integrate a feature to test-run these scripts in a sandboxed environment before deploying them to real-world scenarios. Step 3: Add Advanced Features - Incorporate a library of pre-built scripts covering common web automation tasks (e.g., form submission, data extraction). - Allow users to save their custom scripts for future use and share them with other users. - Implement logging and error handling to help users debug their scripts more effectively. Step 4: User Interface Design - Develop a clean, intuitive UI that guides users through the process of creating and executing scripts. - Include options for setting up different environments (e.g., local testing vs. production). Step 5: Deployment and Testing - Test the application thoroughly in various scenarios to ensure reliability and performance. - Deploy the application either locally or on a server, making it accessible to end-users. The goal is to leverage 'autoscript-hub-sdk' to streamline the setup process for web automation tasks, allowing users to focus on writing effective scripts rather than configuring complex runtime variables.
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