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AI Prompt Guard

AI Prompt Guard

Agent Gateway can inspect and filter LLM requests to prevent prompt injection attacks and block sensitive data like PII from being sent to AI models.

What you’ll build

In this tutorial, you’ll:

  1. Configure prompt guard policies for LLM requests
  2. Block sensitive data like SSNs and email addresses from reaching the LLM
  3. Use both custom regex patterns and built-in patterns for filtering
  4. Test the prompt guard to see requests blocked in real-time

Prerequisites

Step 1: Set up your environment

Create a working directory and set your API key:

mkdir prompt-guard-test && cd prompt-guard-test
export OPENAI_API_KEY=your-api-key-here

Step 2: Create the configuration

Create a config.yaml file with prompt guard policies:

cat > config.yaml << 'EOF'
binds:
- port: 3000
  listeners:
  - routes:
    - backends:
      - ai:
          name: openai
          provider:
            openAI:
              model: gpt-4o-mini
      policies:
        ai:
          promptGuard:
            request:
            # Block Social Security Numbers
            - regex:
                action: reject
                rules:
                - pattern: SSN
                - pattern: Social Security
              rejection:
                status: 400
                headers:
                  set:
                    content-type: "application/json"
                body: |
                  {
                    "error": {
                      "message": "Request rejected: Content contains sensitive information",
                      "type": "invalid_request_error",
                      "code": "content_policy_violation"
                    }
                  }
            # Block email addresses
            - regex:
                action: reject
                rules:
                - builtin: email
              rejection:
                status: 400
                headers:
                  set:
                    content-type: "application/json"
                body: |
                  {
                    "error": {
                      "message": "Request blocked: Contains email address",
                      "type": "invalid_request_error",
                      "code": "pii_detected"
                    }
                  }
        backendAuth:
          key: "$OPENAI_API_KEY"
EOF

Configuration explained

Setting Description
policies.ai.promptGuard The prompt guard policy that inspects LLM requests
request Rules applied to incoming requests before they reach the LLM
regex.action: reject Block requests that match the patterns
regex.rules List of patterns to match against
pattern Custom regex pattern to match
builtin Use a built-in pattern (like email)
rejection Custom response returned when a request is blocked

Step 3: Start Agent Gateway 

agentgateway -f config.yaml

You should see output indicating the gateway is running on port 3000.

Step 4: Test normal requests

In a new terminal, send a normal request:

curl http://localhost:3000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "gpt-4o-mini",
    "messages": [{"role": "user", "content": "Hello, how are you?"}]
  }'

You should receive a normal response from the LLM.

Step 5: Test blocked requests

Block SSN mentions 

curl http://localhost:3000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "gpt-4o-mini",
    "messages": [{"role": "user", "content": "My SSN is 123-45-6789"}]
  }'

Expected response (request blocked by prompt guard):

{
  "error": {
    "message": "Request rejected: Content contains sensitive information",
    "type": "invalid_request_error",
    "code": "content_policy_violation"
  }
}

Block email addresses 

curl http://localhost:3000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "gpt-4o-mini",
    "messages": [{"role": "user", "content": "Contact me at [email protected]"}]
  }'

Expected response (request blocked by prompt guard):

{
  "error": {
    "message": "Request blocked: Contains email address",
    "type": "invalid_request_error",
    "code": "pii_detected"
  }
}

Built-in patterns

Agent Gateway includes built-in patterns for common PII types:

Pattern Description
email Email addresses
phone Phone numbers
ssn Social Security Numbers
credit_card Credit card numbers
ip_address IP addresses

Example using built-in SSN pattern:

- regex:
    action: reject
    rules:
    - builtin: ssn

Custom regex patterns

Add your own regex patterns to catch credentials, secrets, or custom data:

policies:
  ai:
    promptGuard:
      request:
      - regex:
          action: reject
          rules:
          - pattern: "password[=:]\\s*\\S+"
          - pattern: "api[_-]?key[=:]\\s*\\S+"
          - pattern: "secret[=:]\\s*\\S+"
        rejection:
          status: 400
          headers:
            set:
              content-type: "application/json"
          body: |
            {
              "error": {
                "message": "Request contains credentials",
                "type": "invalid_request_error",
                "code": "credentials_detected"
              }
            }

Response filtering

You can also filter LLM responses to mask sensitive data before it reaches the client:

policies:
  ai:
    promptGuard:
      response:
      - regex:
          action: mask
          rules:
          - builtin: credit_card
          replacement: "[REDACTED]"

Cleanup

Stop the Agent Gateway with Ctrl+C and remove the test directory:

cd .. && rm -rf prompt-guard-test

Learn more

LLM Gateway
LLM gateway features
 AI Policies
AI policy configuration reference