How do I secure Hugging Face applications?

Integrate Wardstone Guard with your Hugging Face application to detect prompt injections, jailbreaks, harmful content, and data leakage. Wardstone validates inputs before they reach Hugging Face and screens outputs before returning them to users.

What security risks does Hugging Face have?

Untrusted Model Weights: Community-uploaded models may contain backdoors or be intentionally unsafe. Inconsistent Safety: Different Hub models have wildly different safety training levels. Pickle Deserialization: Model files can contain arbitrary code that executes on load.

Hugging Face + Wardstone

Protect Any Hub Model

Secure any model from the Hugging Face Hub. Wardstone Guard protects Inference Endpoints and self-hosted models with consistent security policies across thousands of model variants.

13 Supported Models· all protected with sub-30ms latency

Inference EndpointsSpacesLlama 4 (all variants)Mistral (all variants)Qwen2.5 (all sizes)Phi-4+7 more

Try the Playground Visit Hugging Face

Why Secure Hugging Face?

Untrusted Model Weights

High Risk

Community-uploaded models may contain backdoors or be intentionally unsafe.

Inconsistent Safety

High Risk

Different Hub models have wildly different safety training levels.

Pickle Deserialization

Medium Risk

Model files can contain arbitrary code that executes on load.

Security Considerations

1
Hub models have varying levels of safety training
2
Community-uploaded models may contain backdoors
3
Inference Endpoints don't include safety filtering by default
4
Wardstone provides consistent security across heterogeneous models

How to Integrate

Add Wardstone to your HF pipeline
Install Wardstone SDK in your Hugging Face inference code.
Validate before inference
Screen all inputs before sending to Inference Endpoints or local models.
Screen model outputs
Validate responses from any Hub model for harmful content.
Implement consistent policies
Apply uniform security policies across different model types.

Pricing Note

Hugging Face pricing varies by deployment type. Wardstone provides uniform security pricing across all HF models.

Secure Hugging Face with Wardstone

# Step 1: Check user input with Wardstone
curl -X POST "https://api.wardstone.ai/v1/detect" \
  -H "Authorization: Bearer YOUR_WARDSTONE_KEY" \
  -H "Content-Type: application/json" \
  -d '{"text": "User message here"}'
 
# Response: { "prompt_attack": { "detected": false, ... } }
 
# Step 2: If safe, send to HuggingFace Inference API
curl -X POST "https://api-inference.huggingface.co/models/meta-llama/Llama-4-Scout-109B-Instruct/v1/chat/completions" \
  -H "Authorization: Bearer YOUR_HF_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "meta-llama/Llama-4-Scout-109B-Instruct",
    "messages": [{"role": "user", "content": "User message here"}],
    "max_tokens": 500
  }'
 
# Step 3: Check HuggingFace response with Wardstone before returning to user

Common Use Cases

Model experimentation and prototyping

Production inference endpoints

Fine-tuned model deployment

Community model access

ML research applications

All Supported Hugging Face Models

Wardstone Guard protects all Hugging Face models with the same comprehensive security coverage. Whether you're using the latest releases or legacy models still in production, every API call is protected.

Inference Endpoints

Spaces

Llama 4 (all variants)

Mistral (all variants)

Qwen2.5 (all sizes)

Phi-4

DeepSeek (all variants)

Gemma 2 (all sizes)

StarCoder2

FLUX.1

Stable Diffusion 3.5

Whisper Large v3