aws-cdk.aws-kinesisanalytics-flink-alpha

v2.258.0a0 safe
2.0
Low Risk

A CDK Construct Library for Kinesis Analytics Flink applications

🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of malicious activity with very low risks across all categories assessed. It is considered safe for use.

  • No network calls detected
  • No shell execution patterns
  • No obfuscation patterns
  • No credential harvesting patterns
Per-check LLM notes
  • Network: No network calls detected, which is normal for a library focused on AWS CDK constructs and not performing direct cloud interactions.
  • Shell: No shell execution patterns detected, which is expected as the package does not involve system-level operations.
  • 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 no other suspicious flags were raised.

📦 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 (4083 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-cdk
  • 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 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-kinesisanalytics-flink-alpha
Create a real-time data processing application using AWS CDK and the 'aws-cdk.aws-kinesisanalytics-flink-alpha' package. This application will demonstrate the power of streaming analytics by processing live stock market tickers. The app will consist of the following components:

1. **Data Source**: Set up a Kinesis Data Stream to ingest real-time stock ticker data.
2. **Processing Engine**: Use Kinesis Data Analytics Flink to process the incoming data streams in real-time, calculating rolling averages and detecting anomalies in stock prices.
3. **Output**: Store the processed data into a Kinesis Data Firehose stream, which then loads the data into an S3 bucket for further analysis.
4. **Visualization**: Integrate with a simple web dashboard (using Flask) to display real-time stock price trends and anomalies detected.

### Features:
- Real-time ingestion and processing of stock ticker data.
- Calculation of rolling averages over a specified time window.
- Detection of stock price anomalies based on deviations from the rolling average.
- Storage of processed data in S3 for historical analysis.
- Web-based visualization of stock price trends and anomalies.

### Utilization of 'aws-cdk.aws-kinesisanalytics-flink-alpha':
- Configure the Kinesis Data Stream as the input source for your Flink application.
- Define a Flink SQL job within the CDK construct to calculate rolling averages and detect anomalies.
- Output the results of the Flink job to a Kinesis Data Firehose delivery stream for archival purposes.

Your task is to design and implement this application using the AWS CDK, focusing on the integration of 'aws-cdk.aws-kinesisanalytics-flink-alpha'. Provide a clear, modular structure for your codebase and ensure that all necessary resources are properly configured and deployed using AWS CDK constructs. Additionally, include instructions for setting up and running the Flask-based web dashboard locally to visualize the processed data.

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