airbyte-source-facebook-pages

v2.1.1 suspicious
4.0
Medium Risk

Source implementation for Facebook Pages.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows moderate signs of obfuscation and requires further scrutiny regarding its handling of access tokens, although it does not exhibit clear malicious behavior.

  • moderate obfuscation risk
  • unclear access token handling
Per-check LLM notes
  • Network: The observed network call pattern is expected as it likely interacts with the Facebook Graph API to fetch data from Facebook Pages.
  • Shell: No shell execution patterns detected, which is normal and expected.
  • Obfuscation: The observed patterns suggest potential obfuscation of sensitive data, possibly to hide the access token retrieval logic.
  • Credentials: No clear signs of direct credential harvesting; however, further analysis is needed to confirm legitimacy of access token handling.
  • Metadata: The author 'Airbyte' has only one package on PyPI, which could indicate a new or less active account, raising some suspicion but not conclusive evidence of malintent.

📦 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 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.airbyte.com/integrations/sources/facebook-pages
  • Brief PyPI description (470 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

  • 6 type-annotated function signatures (partial)
✦ High Multiple Contributors 10.0

Active multi-contributor project

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

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • try: r = requests.get( f"https://graph.facebook.com/{self._page_id
⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

  • ge_id, parameters=parameters).eval(self.config) self._access_token = InterpolatedString
  • token, parameters=parameters).eval(self.config) def __call__(self, request: requests.Prepa
✓ 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 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-source-facebook-pages 
Create a social media analytics dashboard using Python that integrates data from Facebook Pages. This project will utilize the 'airbyte-source-facebook-pages' package to extract data such as page insights, post metrics, and audience demographics. Your task is to develop a user-friendly web application where users can input their Facebook Page ID and view real-time analytics in an interactive format. Here are the key steps and features to include:

1. **Setup**: Begin by installing necessary packages including 'airbyte-source-facebook-pages', 'Flask' for the web framework, and 'Plotly' or 'Matplotlib' for data visualization.
2. **Authentication**: Implement OAuth 2.0 for secure authentication with Facebook's API. Guide users through the process of obtaining access tokens.
3. **Data Extraction**: Use 'airbyte-source-facebook-pages' to fetch data from specified Facebook Pages. Ensure you handle any potential errors gracefully during extraction.
4. **Data Storage & Processing**: Store the extracted data in a local SQLite database. Develop functions to process this data for analysis purposes.
5. **Dashboard Development**: Create a Flask-based web app where users can input their Facebook Page ID. Display the fetched data in a visually appealing manner using Plotly or Matplotlib charts.
6. **Real-Time Updates**: Implement functionality to refresh the displayed data periodically, ensuring users always have the latest information.
7. **Customization Options**: Allow users to customize which metrics they want to track and display on their dashboard.
8. **User Interface Design**: Focus on creating an intuitive UI that makes it easy for users to interact with the app. Include tooltips and help sections explaining different metrics.
9. **Testing & Validation**: Rigorously test the app for bugs and performance issues. Validate that all features work as expected.
10. **Deployment**: Once ready, deploy your application on a platform like Heroku or AWS so others can access it.

This project aims to showcase your ability to integrate external APIs, manage data effectively, and create engaging user interfaces. It also provides valuable insights into social media management and analytics.

💬 Discussion Feed

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