attune-sdk

v0.1.0 suspicious
6.0
Medium Risk

Python SDK for building Attune actions and sensors

🤖 AI Analysis

Final verdict: SUSPICIOUS

The attune-sdk package has been assessed as suspicious due to its metadata risks, including its newness and lack of community engagement. While there are no immediate signs of malicious behavior in terms of network, shell, or obfuscation risks, the package warrants further scrutiny.

  • Metadata risk score of 7/10 indicates potential malicious intent due to package novelty and minimal activity.
  • No direct evidence of malicious activities such as network exploitation, shell execution, or obfuscation was found.
Per-check LLM notes
  • Network: Network calls are expected if the package interacts with external APIs, but further investigation is needed to confirm legitimacy.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows signs of being potentially malicious due to its newness, lack of community engagement, and minimal activity.

📦 Package Quality Overall: Low (4.0/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (7458 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

  • 331 type-annotated function signatures detected in source
○ Low Multiple Contributors 2.0

Single-author or unverifiable project

  • 1 unique contributor(s) across 3 commits in attune-system/python-attune-sdk
  • Single author with few commits — possibly a personal or throwaway project

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

  • httpx self.http = httpx.AsyncClient() self.interval = 10.0 async def poll(s
  • ) return httpx.Client( base_url=self.context.api_url, head
  • ) return httpx.AsyncClient( base_url=self.context.api_url, head
  • e: self._client = httpx.Client( base_url=self._base_url, co
  • context manager for internal httpx.Client (see httpx docs)""" self.get_httpx_client().__exit__(
  • self._async_client = httpx.AsyncClient( base_url=self._base_url, co
✓ Code Obfuscation

No obfuscation patterns detected

✓ 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: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 5.0

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
  • Single contributor with only 3 commit(s) — possibly throwaway account
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • 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 attune-sdk 
Your task is to develop a Python-based mini-application that leverages the 'attune-sdk' package to create both an action and a sensor for monitoring and managing system performance metrics such as CPU usage, memory usage, and disk space. This application will serve as a simple but effective tool for system administrators or developers who need to keep track of critical system resources.

The application should include the following features:
1. A sensor that periodically collects system performance metrics (CPU usage, memory usage, and disk space).
2. An action that sends an alert (via email or SMS) when any of the monitored metrics exceed predefined thresholds.
3. A user-friendly command-line interface (CLI) for configuring the thresholds and viewing the collected data.
4. Optional feature: Integration with a popular cloud service (such as AWS SNS) for sending alerts.

Here's a step-by-step guide on how to implement this application using the 'attune-sdk':
1. Set up your development environment with Python and install the 'attune-sdk'.
2. Use the 'attune-sdk' to define a sensor that gathers the necessary system performance metrics at regular intervals.
3. Implement an action within the 'attune-sdk' framework that triggers an alert when the metrics surpass the configured thresholds.
4. Develop a CLI using Python's built-in modules (like argparse) to allow users to set up the thresholds and view the collected data.
5. Optionally, integrate with a cloud service provider's notification service to send alerts via their APIs.
6. Test the application thoroughly to ensure it functions correctly under various conditions.
7. Document your code and provide instructions on how to run and configure the application.

By completing this project, you'll gain experience in using the 'attune-sdk' to build real-world applications that monitor and manage system resources efficiently.

💬 Discussion Feed

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