airflow-providers-wherobots

v1.7.0 suspicious
5.0
Medium Risk

Airflow extension for communicating with Wherobots Cloud

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits a moderate level of risk due to the execution of potentially harmful shell commands and signs of low maintenance. While there are no immediate indications of malicious intent, the unusual behavior warrants further investigation.

  • Executing system commands like 'airflow db reset --yes' poses a significant risk.
  • Low maintenance and transparency issues suggest potential suspicious activity.
Per-check LLM notes
  • Network: The network calls appear to be standard HTTP requests which could be for API interactions or fetching resources.
  • Shell: Executing system commands like 'airflow db reset --yes' can be risky and is not typically expected behavior in a package, suggesting potential misuse or accidental inclusion.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of malicious credential theft.
  • Metadata: The package shows signs of low maintenance and potential lack of transparency, which could indicate suspicious activity.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 12 test file(s) found

  • Test runner config found: conftest.py
  • Test runner config found: conftest.py
  • 12 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (8224 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

  • 39 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

  • _delay self.session = requests.Session() self.session.mount("https://", HTTPAdapter(max_ret
  • ter": "5.2"}, ) with requests.session() as session: session.mount("https://", HTTPAdapter(
  • "api_key"})], ) with requests.session() as session: resp = session.get("https://example.co
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • ) def clean_airflow_db(): os.system("airflow db reset --yes") @pytest.fixture() def dag():
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: wherobots.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with airflow-providers-wherobots 
Create a mini-application that leverages the 'airflow-providers-wherobots' package to automate the process of scheduling and managing tasks related to robotics operations through the Wherobots Cloud platform. This application will serve as a bridge between Apache Airflow and the Wherobots ecosystem, enabling users to define workflows that include sending commands to robots, retrieving status updates, and handling various robotic tasks efficiently.

**Steps to Develop the Application:**
1. **Setup Environment**: Begin by setting up your development environment with the necessary packages including 'apache-airflow', 'airflow-providers-wherobots', and any other dependencies required for the project.
2. **Define Workflows**: Design a set of sample workflows that demonstrate how different robotic tasks can be scheduled and executed using Airflow. For instance, you could create a workflow that schedules a robot to perform a cleaning task at specific times during the day.
3. **Implement Task Operators**: Use the 'airflow-providers-wherobots' package to implement custom operators that interact with the Wherobots Cloud API. These operators should handle sending commands to robots, fetching their current status, and receiving feedback from the robots after they've completed a task.
4. **Develop a User Interface**: Create a simple user interface (UI) that allows users to input details about the robots they want to manage and schedule tasks through a graphical interface. This UI should also display real-time status updates of the robots.
5. **Testing and Validation**: Test each component of the application thoroughly to ensure that it functions correctly and integrates smoothly with both Apache Airflow and the Wherobots Cloud platform.
6. **Documentation and Deployment**: Document all aspects of the application, including setup instructions, usage guidelines, and best practices. Prepare the application for deployment on a local server or cloud infrastructure.

**Suggested Features:**
- Support for multiple types of robotic tasks such as navigation, object manipulation, and environmental monitoring.
- Real-time monitoring of robot status and task progress within the UI.
- Automated error handling and retry mechanisms for failed tasks.
- Integration with external systems for data collection and analysis.
- Flexible scheduling options to accommodate various operational needs.

💬 Discussion Feed

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