apache-airflow-providers-hashicorp

v4.6.0 safe
3.0
Low Risk

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

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risk indicators and no direct evidence of malicious intent or supply-chain attacks. It is safe for use based on current analysis.

  • Low network and shell risk
  • Minor metadata issues, but not indicative of malice
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires network functionality.
  • Shell: No shell execution patterns detected, indicating no unexpected system command executions.
  • Obfuscation: The observed pattern is likely a standard method for extending module search paths and not indicative of malicious obfuscation.
  • Credentials: No suspicious patterns indicating credential harvesting were detected.
  • Metadata: The package has some minor issues with maintainer history and a non-secure external link, but no clear signs of malice or typosquatting.

📦 Package Quality Overall: Medium (7.8/10)

✦ High Test Suite 9.0

Test suite present — 9 test file(s) found

  • Test runner config found: conftest.py
  • 9 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-has
  • 1 documentation file(s) (e.g. conf.py)
  • Detailed PyPI description (3953 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
  • 17 type-annotated function signatures detected in source
✦ 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-hashicorp 
Create a fully-functional mini-application that leverages the 'apache-airflow-providers-hashicorp' package to manage Terraform state files in a cloud storage bucket using Apache Airflow. This application will serve as a tool for DevOps engineers to automate the process of storing, retrieving, and managing Terraform state files in a centralized location, ensuring consistency and accessibility across different environments.

Step-by-Step Requirements:
1. Setup: Initialize an Apache Airflow environment with the necessary configurations to connect to a cloud storage service (e.g., AWS S3, Google Cloud Storage).
2. Operators Creation: Develop custom operators that interact with the HashiCorp Terraform backend to store and retrieve state files from the cloud storage bucket.
3. DAG Development: Create Directed Acyclic Graphs (DAGs) that use these custom operators to perform tasks such as initializing a new Terraform workspace, applying configuration changes, and destroying resources when no longer needed.
4. State Management: Implement functionality within the DAGs to automatically upload the Terraform state file after each run to ensure it is always up-to-date in the cloud storage.
5. Monitoring & Logging: Integrate logging mechanisms to track the execution of the DAGs and any errors encountered during the state management processes.
6. Security: Ensure all interactions with the cloud storage and Terraform backend are secured using appropriate authentication methods provided by the cloud provider and Terraform.

Suggested Features:
- Automated backups of Terraform state files at regular intervals.
- Notification system to alert users when state files are updated or when there are issues with the Terraform runs.
- Support for multiple Terraform workspaces to manage different environments (e.g., dev, staging, prod).
- Versioning of Terraform state files to allow rollback in case of issues.

How 'apache-airflow-providers-hashicorp' Package is Utilized:
This package provides hooks and operators that enable seamless integration between Apache Airflow and HashiCorp tools like Terraform. It allows for the creation of custom operators within Airflow that can execute Terraform commands, manage state files, and interact with Terraform backends, thus automating the entire lifecycle of infrastructure provisioning and management.

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