automata-linq-sdk

v1.18.0 safe
3.0
Low Risk

(No description)

🤖 AI Analysis

Final verdict: SAFE

Based on the analysis, the package appears to be legitimate with no signs of malicious intent. The network calls seem to be for OAuth token retrieval and API access, which are common practices for packages that interact with external services.

  • Network calls are likely for OAuth token retrieval and API access
  • No shell execution, obfuscation, or credential harvesting patterns detected
  • Author has only one package, suggesting it may be from a new or less active developer
Per-check LLM notes
  • Network: The network calls appear to be related to OAuth token retrieval and API access, which could be legitimate if the package is designed to interact with an external service using OAuth authentication.
  • 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 author has only one package, which might indicate a new or less active user, but there are no other suspicious flags.

📦 Package Quality Overall: Low (3.8/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

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

Some documentation present

  • Brief PyPI description (360 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

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

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

  • happen." token_response = requests.post( f"https://{auth0_domain}/oauth/token", head
  • omain}" token_response = requests.post( f"https://{auth0_domain}/oauth/token", head
  • ize self._response = requests.get(self.url, stream=True) self._response.raise_for_stat
✓ 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

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Automata" 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 automata-linq-sdk 
Create a Python-based mini-application called 'Automata Query Tool' that leverages the Automata LINQ SDK to interact with a hypothetical database of user profiles. This tool should allow users to perform complex queries on a dataset containing information such as user ID, username, email, age, and location. The application should provide a command-line interface where users can input LINQ-like queries to retrieve specific subsets of data based on criteria like age range, location, and username patterns.

### Key Features:
- **Query Execution:** Users should be able to enter LINQ-like query strings to filter the dataset.
- **Sorting:** Implement sorting options to sort the results based on any field (e.g., alphabetical order by username).
- **Pagination:** Introduce pagination to handle large datasets efficiently.
- **Error Handling:** Gracefully handle invalid inputs and errors from the SDK.
- **Help Menu:** Include a help menu that explains basic query syntax and available fields.

### Utilizing Automata LINQ SDK:
- Use the SDK's core functionalities to parse and execute LINQ queries against the provided dataset.
- Ensure that the SDK is properly integrated into your application to facilitate seamless interaction with the dataset.
- Explore the SDK documentation to understand how to structure queries and handle returned results.

### Development Steps:
1. **Setup Environment:** Install necessary packages including Automata LINQ SDK via pip.
2. **Data Preparation:** Create a mock dataset of user profiles to work with.
3. **CLI Interface:** Develop a command-line interface for user interaction.
4. **Query Parsing & Execution:** Implement functionality to parse and execute LINQ-like queries using the SDK.
5. **Enhancements:** Add sorting, pagination, and error handling mechanisms.
6. **Testing:** Test the application thoroughly to ensure all features work as expected.
7. **Documentation:** Provide clear instructions on how to use the application and run tests.

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