ariadne-core-client

v0.1.0 suspicious
6.0
Medium Risk

Python client for Ariadne Core document extraction and retrieval API

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits high risks related to shell execution and credential handling, with no documentation to clarify its intended use. This combination raises concerns about potential malicious intent.

  • High shell risk due to potential for executing arbitrary code
  • High credential risk suggesting possible credential harvesting
Per-check LLM notes
  • Network: The network pattern suggests local connection attempts which could be benign if part of the package's functionality, but may indicate unusual behavior if not documented.
  • Shell: Executing scripts as subprocesses can be legitimate, but it poses a risk of executing arbitrary code, especially if input is not properly sanitized.
  • Obfuscation: No obfuscation patterns detected.
  • Credentials: Suspicious strings indicating potential credential harvesting activities.

📦 Package Quality Overall: Low (3.6/10)

✦ High Test Suite 9.0

Test suite present — 9 test file(s) found

  • Test runner config found: conftest.py
  • 9 test file(s) detected (e.g. conftest.py)
○ Low Documentation 1.0

No documentation detected

  • No documentation URL, doc files, or meaningful description found
○ 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

  • 178 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 6.0

Found 4 network call pattern(s)

  • try: with socket.create_connection(("127.0.0.1", port), timeout=0.2): brea
  • client. Stdlib-only: uses urllib.request. Maps HTTP errors to the exception classes defined in excep
  • parsed.netloc`` and is what ``urllib.request.Request.host`` # returns when ``urlopen`` connect
  • userinfo, and ``urllib.request.Request.host`` returns the polluted netloc. Both
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 6.0

Found 3 shell execution pattern(s)

  • update(extra_env) return subprocess.run( [sys.executable, "-m", "ariadne_core_client.cli",
  • the script as a subprocess (``subprocess.run([sys.executable, script_path], env=..., capture_output=True
  • affect. """ return subprocess.run( # noqa: S603 — controlled args [sys.executable, s
⚠ Credential Harvesting score 2.5

Found 1 credential access pattern(s)

  • le.com", "file:///etc/passwd", "javascript:alert(1)", "ftp://e
✓ 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 6.0

3 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author "Denson Smith" 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 ariadne-core-client 
Create a document management tool named 'DocManager' using Python that leverages the 'ariadne-core-client' package for document extraction and retrieval. This tool will enable users to upload various types of documents (PDFs, Word Docs, etc.), extract key information from these documents, and manage a searchable database of document metadata and extracted content.

Step 1: Setup the Project
- Initialize a new Python project.
- Install 'ariadne-core-client' and other necessary packages like Flask for the web interface.

Step 2: Design the User Interface
- Develop a simple web interface using Flask where users can upload documents.
- Include options for users to search through previously uploaded documents based on extracted metadata.

Step 3: Implement Document Upload Functionality
- Use 'ariadne-core-client' to handle the uploading process and ensure documents are stored securely.

Step 4: Extract Information from Documents
- Utilize 'ariadne-core-client' to extract key information such as author names, dates, and specific content snippets from the uploaded documents.
- Store this information in a structured format, such as SQLite or PostgreSQL, for easy querying.

Step 5: Create Search Functionality
- Implement a search feature that allows users to find documents based on keywords or metadata.
- Display results in a user-friendly manner, showing relevant excerpts from the documents.

Suggested Features:
- Support for multiple file formats (PDF, DOCX, TXT).
- Ability to tag documents for easier categorization.
- Integration with a cloud storage service for secure document backup.
- Detailed analytics on document usage patterns.

How 'ariadne-core-client' is Utilized:
- For document uploading and handling the communication with the Ariadne Core API.
- For extracting information from documents, which includes text recognition, metadata extraction, and content analysis.

💬 Discussion Feed

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