apache-airflow-providers-cohere

v1.6.5 safe
3.0
Low Risk

Provider package apache-airflow-providers-cohere for Apache Airflow

🤖 AI Analysis

Final verdict: SAFE

The package shows low risks across multiple checks with no clear indicators of malicious behavior or supply-chain attacks.

  • Low credential risk
  • No signs of obfuscation
  • Minor metadata concerns but benign
Per-check LLM notes
  • Obfuscation: The observed pattern is likely a standard method for extending module search paths and not indicative of malicious obfuscation.
  • Credentials: No patterns indicative of credential harvesting were detected.
  • Metadata: The package shows some minor red flags but lacks clear indicators of malicious intent.

📦 Package Quality Overall: Medium (7.8/10)

✦ High Test Suite 9.0

Test suite present — 10 test file(s) found

  • Test runner config found: conftest.py
  • 10 test file(s) detected (e.g. conftest.py)
✦ High Documentation 9.0

Well-documented package

  • Documentation URL: "Documentation" -> https://airflow.apache.org/docs/apache-airflow-providers-coh
  • 1 documentation file(s) (e.g. conf.py)
  • Detailed PyPI description (3821 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Type checker (mypy / pyright / pytype) referenced in project
  • 5 type-annotated function signatures (partial)
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 46 unique contributor(s) across 100 commits in apache/airflow
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

  • under the License. __path__ = __import__("pkgutil").extend_path(__path__, __name__) # Licensed to the Apache S
✓ 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: airflow.apache.org>

⚠ Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://www.apache.org/licenses/LICENSE-2.0
✓ Git Repository History

Repository apache/airflow appears legitimate

⚠ 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 apache-airflow-providers-cohere 
Create a mini-application using Apache Airflow and the 'apache-airflow-providers-cohere' package that automates the process of generating creative content based on user input. This application will allow users to submit a topic or a seed phrase, and the system will use Cohere's AI capabilities to generate a piece of content around that topic. The application should have the following features:

1. User Interface: A simple web interface where users can input their topic/seed phrase and initiate the content generation process.
2. Workflow Management: Use Apache Airflow to manage the workflow from receiving user input to generating and delivering the final content.
3. Content Generation: Utilize the 'apache-airflow-providers-cohere' package to integrate Cohere's API into your workflow, enabling the AI to generate high-quality content.
4. Notification System: Once the content is generated, notify the user via email about the completion of the task and provide a link to view/download the generated content.
5. Logging & Monitoring: Implement logging to track the status of each job and monitoring to ensure the system is running smoothly.
6. Security Measures: Ensure all data transmissions are secure and that sensitive information is handled according to best practices.

The 'apache-airflow-providers-cohere' package will be crucial in connecting your Apache Airflow DAGs with Cohere's API endpoints, allowing for seamless integration between your workflow management system and the AI content generation service. Your task is to design and implement this mini-application, ensuring it is both functional and user-friendly.

💬 Discussion Feed

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