apache-airflow-providers-imap

v3.11.3 safe
3.0
Low Risk

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

🤖 AI Analysis

Final verdict: SAFE

The package shows low risks across all categories with only minor issues in metadata and obfuscation. There are no indications of malicious activities or supply-chain attacks.

  • Low network and shell execution risks.
  • Minor obfuscation and metadata concerns, but no strong signs of malice.
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communications.
  • Shell: No shell execution patterns detected, indicating no unexpected system command executions.
  • Obfuscation: The observed pattern is a common technique for extending module search paths and does not indicate malicious obfuscation.
  • Credentials: No suspicious patterns indicative of credential harvesting were found.
  • Metadata: The package has some minor issues with maintainer history and a non-HTTPS link, but no strong indicators of malicious activity.

📦 Package Quality Overall: Medium (7.8/10)

✦ High Test Suite 9.0

Test suite present — 7 test file(s) found

  • Test runner config found: conftest.py
  • 7 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-ima
  • 1 documentation file(s) (e.g. conf.py)
  • Detailed PyPI description (3456 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
  • 22 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 4.0

Found 2 obfuscation pattern(s)

  • under the License. __path__ = __import__("pkgutil").extend_path(__path__, __name__) # Licensed to the Apache S
  • under the License. __path__ = __import__("pkgutil").extend_path(__path__, __name__) # # Licensed to the Apache
✓ 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-imap 
Create a fully-functional mini-application using Apache Airflow and the 'apache-airflow-providers-imap' package to automate email processing tasks. This application will serve as an email monitoring tool designed to check for specific keywords in incoming emails from a specified IMAP server and trigger actions based on those keywords.

### Step-by-Step Guide:
1. **Setup Environment**: Ensure you have Apache Airflow installed along with the 'apache-airflow-providers-imap' package. Set up your Airflow environment properly to include the IMAP provider.
2. **Define DAGs**: Create one or more Directed Acyclic Graphs (DAGs) that define the workflow of your email processing tasks. Each DAG will represent a different set of rules or actions related to email handling.
3. **Email Monitoring Task**: Implement a task within the DAG that connects to an IMAP server, retrieves new emails, and searches for specific keywords in the email bodies. Use the 'apache-airflow-providers-imap' package to facilitate this connection and interaction.
4. **Action Triggers**: Based on the presence of certain keywords in the email content, trigger corresponding actions. These actions could include sending alerts, updating databases, or initiating other workflows within Airflow.
5. **Error Handling & Logging**: Include robust error handling and logging mechanisms to ensure that any issues encountered during email processing are captured and can be reviewed later.
6. **Testing & Validation**: Thoroughly test the application using simulated emails to verify that it correctly identifies the relevant keywords and triggers the appropriate actions.
7. **Deployment & Maintenance**: Once tested, deploy the application in a production-like environment and establish a plan for ongoing maintenance and updates.

### Suggested Features:
- **Keyword Filters**: Allow users to specify multiple keywords and filter emails based on these criteria.
- **Flexible Actions**: Provide a range of actions that can be triggered upon keyword detection, such as sending notifications, archiving emails, or invoking external APIs.
- **Configuration Management**: Enable easy configuration management for the IMAP server details and other parameters via Airflow's configuration system.
- **Performance Metrics**: Incorporate performance metrics to monitor the efficiency of the email processing tasks and identify bottlenecks if they occur.

By following these steps and incorporating the suggested features, you'll develop a powerful and flexible email monitoring tool that leverages the capabilities of Apache Airflow and the 'apache-airflow-providers-imap' package.

💬 Discussion Feed

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