AI Analysis
Final verdict: SAFE
The package shows low activity and minimal risks across all assessed categories, with no indications of malicious behavior.
- No network calls or shell executions detected.
- No signs of obfuscation or credential harvesting.
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires network interactions for its functionality.
- Shell: No shell execution patterns detected, indicating no immediate risk of command injection or similar attacks.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
- Credentials: No credential harvesting patterns detected, suggesting safe handling of sensitive information.
- Metadata: The package shows low activity signs, but no clear malicious indicators.
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
score 2.5
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Yusuf Karamuk" 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 actionaudit
Create a Python-based web application called 'GitHub Action Security Monitor' which integrates the 'actionaudit' package to provide users with a comprehensive security analysis of their GitHub Actions workflows. This application will allow users to upload their workflow files (.yml or .yaml) and receive detailed reports on potential security risks and compliance issues. Here are the key steps and features your application should include: 1. **User Interface**: Design a simple, user-friendly interface using Flask or Django where users can upload their GitHub Actions workflow files. 2. **File Upload Handling**: Implement file upload functionality that accepts .yml or .yaml files. Ensure that only these file types are allowed to prevent any security vulnerabilities. 3. **Security Analysis**: Utilize the 'actionaudit' package to analyze the uploaded workflows. Integrate its core functionalities to scan for common security issues such as insecure permissions, use of untrusted actions, and missing secrets management. 4. **Report Generation**: After the analysis, generate a detailed report for each uploaded workflow. This report should include a summary of findings, severity levels (low, medium, high), and actionable recommendations for improving security. 5. **Visualization**: Use libraries like Matplotlib or Plotly to visualize the severity distribution of detected issues in the report. 6. **Email Notification**: Implement a feature where users can choose to receive the report via email after uploading their workflow file. Ensure secure handling of email credentials and user data. 7. **Documentation**: Provide clear documentation on how to install and use the application, including setup instructions for deploying it on a server or cloud platform. 8. **Testing**: Write unit tests for the backend logic and integration tests to ensure the 'actionaudit' package is correctly integrated and functioning as expected. 9. **Deployment**: Plan for deployment on platforms like Heroku or AWS, ensuring scalability and security best practices are followed. This project aims to bridge the gap between static code analysis tools and the unique security needs of GitHub Actions workflows, providing developers with a powerful tool to enhance their CI/CD pipeline security.