airbyte-cdk

v7.21.0 safe
3.0
Low Risk

A framework for writing Airbyte Connectors.

🤖 AI Analysis

Final verdict: SAFE

The package shows some minor concerns regarding network calls and potential obfuscation techniques, but there are no clear signs of malicious activity or credential risks. Overall, the package appears safe.

  • Potential misuse of eval() function
  • Network call to unknown URL
Per-check LLM notes
  • Network: The network call to fetch mask keys is likely for legitimate masking purposes, but it should be reviewed for where the URL points and what data is being sent/received.
  • Shell: No shell execution patterns detected.
  • Obfuscation: The code appears to be using eval() on fields that may be user-configurable, which could indicate an attempt at obfuscation or code injection, but it's not conclusive without more context.
  • Credentials: No clear patterns of credential harvesting were detected in the provided snippets.
  • Metadata: The author has only one package, which might indicate a new or less active account, but no other red flags are present.

📦 Package Quality Overall: Medium (6.6/10)

✦ High Test Suite 9.0

Test suite present — 1 test file(s) found

  • Test runner config found: pyproject.toml
  • 1 test file(s) detected (e.g. test_utils.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.airbyte.io/
  • Detailed PyPI description (2780 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

  • 284 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 20 unique contributor(s) across 100 commits in airbytehq/airbyte-python-cdk
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • mask file.""" response = requests.get(GLOBAL_MASK_KEYS_URL, allow_redirects=True) if not respo
⚠ Code Obfuscation score 10.0

Found 6 obfuscation pattern(s)

  • r = self._stream_cursor_field.eval(self.config) # type: ignore # _stream_cursor_field is alway
  • .step, parameters=parameters).eval(self.config) ) if self.step
  • return {self.cursor_field.eval(self.config): self._cursor} if self._cursor else {} # type:
  • m_state.get(self.cursor_field.eval(self.config)) if stream_state else None # type: ignore [uni
  • record.get(self.cursor_field.eval(self.config)) # type: ignore # cursor_field is converted t
  • = self._partition_field_start.eval(self.config) end_field = self._partition_field_end.e
✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: airbyte.io

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository airbytehq/airbyte-python-cdk appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Airbyte" 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 airbyte-cdk 
Your task is to develop a simple data integration tool using the 'airbyte-cdk' Python package. This tool will serve as a bridge between a source database (MySQL) and a destination storage service (S3). Your goal is to create a custom connector that periodically extracts data from a MySQL database table and loads it into an S3 bucket in CSV format. Here’s a detailed breakdown of the requirements and steps you need to follow:

1. **Setup Project Environment**: Initialize a new Python project and install the necessary dependencies including 'airbyte-cdk'. Ensure your environment supports Python 3.8 or higher.

2. **Define Connector Configuration**: Design a configuration schema for your connector that allows users to specify MySQL connection details (host, port, username, password, database name) and S3 credentials (access key, secret key, bucket name).

3. **Implement Source and Destination Interfaces**: Use 'airbyte-cdk' to define interfaces for reading data from MySQL and writing data to S3. Implement these interfaces with functions that connect to the respective services and perform the required operations.

4. **Data Extraction and Transformation**: Write logic within your connector to extract data from a specific MySQL table. Include functionality to handle errors and retries during extraction. Additionally, implement basic transformation logic to convert the extracted data into CSV format before uploading to S3.

5. **Periodic Syncs**: Integrate a scheduler (such as cron jobs) into your connector so that it can run periodic syncs at specified intervals (e.g., every hour).

6. **Testing and Validation**: Develop unit tests for each function within your connector to ensure reliability. Also, include validation checks to confirm that data successfully transfers from MySQL to S3 and retains integrity throughout the process.

7. **Documentation**: Provide comprehensive documentation detailing how to configure and use your connector. Include examples of typical usage scenarios and troubleshooting tips.

By following these steps, you'll create a robust, user-friendly data migration tool leveraging the capabilities of 'airbyte-cdk', demonstrating its utility in real-world data integration tasks.