AI Analysis
Final verdict: SAFE
The package is deemed safe with low risks across all categories, including network, shell, obfuscation, and credential risks. The metadata risk is slightly elevated due to the author's limited presence, but there are no other red flags.
- No network or shell execution detected.
- No obfuscation or credential harvesting patterns observed.
- Author has only one package, potentially indicating a new or less active account.
Per-check LLM notes
- Network: No network calls detected, which is normal for a package that doesn't require internet access to function.
- Shell: No shell execution patterns detected, which is expected as the package likely does not need to execute system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The author has only one package, which may indicate a new or less active account, but there are no other suspicious flags.
Package Quality Overall: Medium (5.0/10)
○ 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 (12401 chars)
○ Low
Contributing Guide
4.0
No contributing guide or governance files found
Development Status classifier >= Beta
◈ Medium
Type Annotations
5.0
Partial type annotation coverage
Classifier: Typing :: Typed
✦ High
Multiple Contributors
10.0
Active multi-contributor project
32 unique contributor(s) across 100 commits in aws/aws-cdkActive community — 5 or more distinct contributors
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
Repository aws/aws-cdk appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Amazon Web Services" 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 aws-cdk.aws-apprunner-alpha
Create a fully-functional mini-application using the AWS CDK with the 'aws-cdk.aws-apprunner-alpha' package to deploy a simple web application. This project will serve as a basic introduction to deploying applications on AWS App Runner using the AWS CDK constructs. Here’s a step-by-step guide on what your application should accomplish: 1. **Project Setup**: Initialize a new Python project and install the necessary dependencies including 'aws-cdk-lib', 'constructs', and 'aws-cdk.aws-apprunner-alpha'. Ensure your AWS credentials are correctly configured. 2. **Define Application Components**: - Create a Docker image for a simple Flask-based web application that serves a single page with a greeting message. - Use the 'aws-apprunner-alpha' package to define an App Runner service that will run this Docker image. 3. **Deployment Automation**: Write a script that builds the Docker image locally and then deploys it using the AWS CDK constructs. The deployment process should automatically trigger the creation of the App Runner service. 4. **Environment Configuration**: Allow for environment variables to be passed into the App Runner service so that the greeting message can be customized based on these variables. 5. **Testing and Validation**: After deployment, write a simple test script to validate that the App Runner service is up and running, and that the greeting message reflects the custom environment variable settings. 6. **Cleanup Script**: Include a cleanup script that can destroy all resources created during the deployment process to ensure no unnecessary costs are incurred. Suggested Features: - Implement CI/CD integration with GitHub Actions or AWS CodePipeline to automate the build and deployment process. - Add logging capabilities to monitor the App Runner service’s health and performance. - Integrate a simple user interface to allow users to change the greeting message without redeploying the application. This project will not only demonstrate the power of AWS CDK and AWS App Runner but also provide a practical example of serverless application development and deployment.
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