ambient-toolbox

v12.10.3 suspicious
4.0
Medium Risk

Python toolbox of Ambient Digital containing an abundance of useful tools and gadgets.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows moderate risks, particularly in network and shell command usage, but lacks clear indicators of malicious intent. The metadata and obfuscation risks are low.

  • Moderate network risk
  • Higher than average shell risk
Per-check LLM notes
  • Network: The network calls appear to be fetching status codes from URLs which could be related to CI/CD pipelines or job statuses.
  • Shell: The use of shell commands and subprocess calls may indicate legitimate functionality but also poses higher risk due to potential execution of arbitrary commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, indicating secure handling of secrets.
  • Metadata: The maintainer has a new or inactive account and lacks a full author name, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Medium (7.0/10)

✦ High Test Suite 9.0

Test suite present — 1 test file(s) found

  • Test runner config found: pyproject.toml
  • 1 test file(s) detected (e.g. base_test.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Changelog" -> https://ambient-toolbox.readthedocs.io/en/latest/features/ch
  • Detailed PyPI description (4276 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 31 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 6 unique contributor(s) across 100 commits in ambient-innovation/ambient-toolbox
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

  • sha={sha}" response = httpx.get(pipeline_url) status_code = response.status_code
  • rl}") jobs_response = httpx.get(jobs_with_token_url) jobs_status_code = jobs_respons
  • " pipeline_response = httpx.get(pipeline_with_token_url) pipeline_status_code = pipe
  • oken}" job_response = httpx.get(job_with_token_url) job_status_code = job_response.s
  • son.") response = httpx.get(self.pipelines_url_with_token) status_code = res
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • """ result = subprocess.run( # noqa: PLW1510 ["git", "merge-base", "--fork-
  • ations") output = subprocess.call(f'grep -q "#, fuzzy" {translation_file_path}', shell=True)
  • ations") output = subprocess.call(f'grep -q "#~" {translation_file_path}', shell=True)
  • try: subprocess.call(f"python manage.py create_translation_file --lang {lang}", s
  • le") output = subprocess.call( f"git diff --no-index --ignore-matching
  • slated") output = subprocess.call( f"msgattrib --untranslated ./locale/{lang}/
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: ambient.digital>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository ambient-innovation/ambient-toolbox 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 ambient-toolbox 
Create a fully-functional weather monitoring and analysis mini-app using the 'ambient-toolbox' Python package. This app will serve as a user-friendly tool for tracking weather conditions in real-time and analyzing historical weather data. Here are the steps and features you should include in your project:

1. **Setup**: Begin by installing the 'ambient-toolbox' package. Ensure that the setup includes all necessary dependencies and configurations required for accessing real-time and historical weather data.

2. **Real-Time Weather Monitoring**: Implement a feature that fetches real-time weather updates from various sources supported by the 'ambient-toolbox'. This should include temperature, humidity, wind speed, and direction, among other parameters. Display these details in a clear and user-friendly format.

3. **Historical Data Analysis**: Utilize the 'ambient-toolbox' to access historical weather data. Implement functionalities to visualize trends over different periods such as daily, weekly, monthly, or yearly. Allow users to select specific dates or periods to analyze.

4. **Forecasting Tools**: Integrate a forecasting module that predicts future weather conditions based on past data. Use statistical models provided by the 'ambient-toolbox' or any other relevant libraries it supports.

5. **User Interface**: Design a simple yet effective GUI using a library like Tkinter or PyQt, which interacts seamlessly with the 'ambient-toolbox'. The UI should allow easy navigation through real-time and historical data, as well as forecast predictions.

6. **Data Export**: Enable users to export analyzed data into CSV or Excel formats for further analysis or record-keeping.

7. **Alert System**: Implement an alert system that notifies users via email or SMS when certain weather thresholds are met (e.g., extreme temperatures, heavy rainfall).

8. **Documentation & Testing**: Provide comprehensive documentation for each feature and ensure thorough testing across multiple platforms and devices.

By following these steps and incorporating the suggested features, your mini-app will become a valuable tool for anyone interested in monitoring and understanding weather patterns.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!