How do I secure Ollama applications?

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

Ollama + Wardstone

Secure Local AI Deployments

Protect your local Ollama deployments with Wardstone Guard. Add production-grade security to self-hosted models running on your own infrastructure.

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

Llama 4 ScoutLlama 4 MaverickLlama 3.3 70BLlama 3.2 (all sizes)Qwen2.5 (all sizes)Qwen2.5-Coder+9 more

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Why Secure Ollama?

Zero External Safety

High Risk

Local models have no provider-side safety filtering whatsoever.

Unvetted Models

High Risk

Community GGUF models may contain backdoors or be intentionally unsafe.

Local Network Exposure

Medium Risk

Ollama's default configuration can expose models to the local network.

Security Considerations

1
Local deployment means no cloud provider safety filters
2
Community models may have unknown vulnerabilities
3
Ollama focuses on ease of use, not security
4
Wardstone can run locally alongside Ollama for air-gapped security

How to Integrate

Run Wardstone locally
Deploy Wardstone alongside Ollama on your local infrastructure.
Proxy Ollama requests
Route requests through Wardstone before they reach Ollama.
Validate all inputs
Screen prompts for attacks before local model inference.
Screen local model outputs
Validate responses from any Ollama model for harmful content.

Pricing Note

Ollama is free. Your costs are hardware. Wardstone adds security to your free local AI setup.

Secure Ollama 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 local Ollama
curl -X POST "http://localhost:11434/api/chat" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "llama4",
    "messages": [{"role": "user", "content": "User message here"}],
    "stream": false
  }'
 
# Step 3: Check Ollama response with Wardstone before returning to user

Common Use Cases

Air-gapped deployments

Local development and testing

Privacy-sensitive applications

Edge AI deployments

Offline AI applications

All Supported Ollama Models

Wardstone Guard protects all Ollama 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.

Llama 4 Scout

Llama 4 Maverick

Llama 3.3 70B

Llama 3.2 (all sizes)

Qwen2.5 (all sizes)

Qwen2.5-Coder

DeepSeek-V3

DeepSeek-R1

DeepSeek-Coder-V2

Mistral Large

Mistral Nemo

Phi-4