huggingface-api-haystack

v0.1.0 suspicious
4.0
Medium Risk

Haystack integration for Hugging Face API

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows no signs of obfuscation or credential harvesting, but its metadata suggests it may pose a risk due to the lack of maintainer history and author details.

  • Low obfuscation risk
  • Low credential risk
  • High metadata risk due to new package and lack of maintainer details
Per-check LLM notes
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package is newly created with limited information and could potentially be malicious due to the lack of maintainer history and author details.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ 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: deepset.ai>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository deepset-ai/haystack-core-integrations appears legitimate

⚠ Maintainer History score 8.0

4 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Package uploaded less than 24 hours ago (2026-06-05T09:33:24.000Z)
  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)

💡 AI App Starter Prompt

Use this prompt to build a project with huggingface-api-haystack 
Create a document question-answering system using the Hugging Face API Haystack integration package. This application will allow users to upload various documents (PDFs, Word docs, etc.) and then ask questions about the content of those documents. The system should provide accurate answers based on the information contained within the uploaded files.

Steps to develop this application:
1. Set up a basic Flask web server as the backend.
2. Integrate the 'huggingface-api-haystack' package to handle the document indexing and querying processes.
3. Implement a user-friendly front-end interface where users can upload their documents and input their questions.
4. Ensure the system supports multiple file formats (e.g., PDF, DOCX, TXT).
5. Optimize the system to handle large documents efficiently without compromising speed or accuracy.
6. Include a feature to visualize the context from which the answer was derived, enhancing transparency and trustworthiness of the responses.
7. Add error handling and feedback mechanisms for when the system cannot find a suitable answer.

Suggested Features:
- Support for real-time preview of the uploaded documents before indexing.
- Option to highlight relevant sections in the original document when displaying answers.
- Integration with a simple authentication system to allow users to save and retrieve their previous queries and results.
- Ability to switch between different models provided by Hugging Face to compare performance and accuracy.

The 'huggingface-api-haystack' package will be used primarily for its capabilities in indexing structured and unstructured data from various sources, as well as its ability to query these indices using natural language processing techniques. By leveraging this package, the application aims to offer a seamless experience for users looking to extract insights from their documents through conversational interactions.