aws-cdk.lambda-layer-kubectl-v35

v2.2.2 safe
1.0
Low Risk

A Lambda Layer that contains kubectl v1.35

⚠ Tarball exceeded 25 MB — source code analysis was limited to package metadata only.

🤖 AI Analysis

Final verdict: SAFE

The package is considered safe based on the low risk scores for network, shell, obfuscation, and credential risks. The metadata risk is slightly elevated but does not indicate any malicious intent.

  • No network or shell risks detected.
  • No signs of code obfuscation or credential mishandling.
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require internet access.
  • Shell: No shell execution patterns detected, which is expected as typical Python packages avoid direct system command executions.
  • Obfuscation: No obfuscation patterns detected, indicating normal and transparent code practices.
  • Credentials: No credential harvesting patterns detected, suggesting safe handling of sensitive information.
  • Metadata: The author appears to be associated with Amazon Web Services and there are no other red 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 (883 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

  • 6 unique contributor(s) across 100 commits in cdklabs/awscdk-asset-kubectl
  • Active 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 cdklabs/awscdk-asset-kubectl appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Amazon Web Services<[email protected]>" 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.lambda-layer-kubectl-v35 
Create a fully-functional mini-application called 'KubeOpsDashboard' that allows users to interact with their Kubernetes clusters directly from a web interface using AWS Lambda functions enhanced with the 'aws-cdk.lambda-layer-kubectl-v35' package. This package includes kubectl v1.35, which will be used to execute Kubernetes commands remotely via the Lambda function.

The application should have the following core functionalities:
- Authenticate users via an OAuth provider of your choice (e.g., Google, GitHub).
- Allow authenticated users to select their Kubernetes cluster from a list of configured clusters.
- Execute common Kubernetes operations such as listing pods, services, deployments, etc., and display the results on the web interface.
- Provide a feature to deploy a simple example application to the selected cluster with a single click.

Steps to develop the application:
1. Set up an AWS account and configure necessary permissions for deploying resources.
2. Use the AWS CDK to create a Lambda layer that includes the 'aws-cdk.lambda-layer-kubectl-v35' package.
3. Develop the Lambda function that interacts with Kubernetes clusters using the kubectl command-line tool provided by the layer.
4. Build a web frontend using a framework like React or Vue.js that communicates with the Lambda function via API Gateway.
5. Implement user authentication using OAuth and secure the API Gateway endpoints.
6. Test the application thoroughly to ensure it works as expected with different Kubernetes clusters.
7. Deploy the application to AWS and provide documentation for setting up and using the KubeOpsDashboard.

This project will showcase the power of serverless architectures in managing Kubernetes clusters and the ease of integrating external tools like kubectl into AWS Lambda functions.

💬 Discussion Feed

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