aws-python-helper

v1.0.3 suspicious
6.0
Medium Risk

AWS Python Helper Framework

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows signs of legitimate functionality but has notable issues with credential risk and metadata availability, suggesting potential misuse or supply-chain attack.

  • High credential risk due to potential improper handling
  • Sparse maintainer information and missing repository
Per-check LLM notes
  • Network: Network calls to AWS services are likely expected for an AWS helper package.
  • Shell: No shell execution patterns detected.
  • Obfuscation: Base64 decoding is commonly used for data obfuscation but can also be legitimate depending on the context.
  • Credentials: Use of environment variables for AWS credentials is standard practice, but lack of proper validation and handling may indicate potential risks.
  • Metadata: The repository is not found and the maintainer's information is sparse, raising concerns about its legitimacy.

📦 Package Quality Overall: Low (3.2/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/fabiae/aws-python-framework/blob/main/REA
  • Detailed PyPI description (67839 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 99 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • try: async with httpx.AsyncClient(timeout=self._timeout) as client: response =
⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

  • decoded = base64.b64decode(session_str).decode('utf-8') return Sess
✓ Shell / Subprocess Execution

No shell execution patterns detected

⚠ Credential Harvesting score 10.0

Found 4 credential access pattern(s)

  • self.region = region or os.getenv('AWS_REGION') if not self.region: raise Valu
  • , region_name=os.getenv("AWS_REGION", "us-east-2"), ) return self._cl
  • base_url = f"https://sqs.{os.getenv('AWS_REGION')}.amazonaws.com/{os.getenv('AWS_ACCOUNT_ID')}"
  • 'AWS_REGION')}.amazonaws.com/{os.getenv('AWS_ACCOUNT_ID')}" queue_name = f"{os.getenv('SERVICE_NA
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" 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-python-helper 
Imagine you're tasked with developing a simple yet powerful utility that helps manage Amazon S3 buckets more efficiently. Your goal is to create a command-line interface (CLI) tool using Python that leverages the 'aws-python-helper' package to interact with AWS S3 services. This tool will allow users to perform various operations on their S3 buckets, such as listing all buckets, uploading files, downloading files, deleting files, and checking the size of a specific bucket. Additionally, the tool should include advanced features like logging, error handling, and user authentication to ensure secure and reliable operation.

Here's a detailed breakdown of what your CLI tool should achieve:
1. **User Authentication**: Implement a mechanism for users to securely authenticate themselves using AWS credentials. Use the 'aws-python-helper' package to handle these credentials and establish a secure connection to AWS S3.
2. **Bucket Management**: Allow users to list all available S3 buckets in their account. Users should also be able to create new buckets if they don't already exist.
3. **File Operations**: Enable users to upload files from their local machine to any specified S3 bucket. Additionally, provide functionality to download files from S3 to the local machine and delete files from S3.
4. **Advanced Features**: Include options to check the size of a specific bucket, which involves fetching metadata about the bucket's contents. Also, implement robust error handling and logging to capture any issues during execution.
5. **Documentation and Testing**: Ensure your code is well-documented and includes unit tests to validate the functionality of each feature.

The 'aws-python-helper' package simplifies interactions with AWS services, providing a structured way to handle tasks such as authentication, bucket operations, file transfers, and more. Utilize its core functionalities to streamline the development process and enhance the reliability of your CLI tool. By the end of this project, you'll have a fully functional, secure, and efficient utility for managing AWS S3 resources.

💬 Discussion Feed

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